基于背景模型的监控视频编码研究
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摘要
视频监控是继数字电视、视频会议之后的一个新的大型视频应用，是视频技术和网络技术经过多年高速发展之后汇聚而成的一个具有变革性的大型信息系统。然而，长时间（数月甚至数年）拍摄的海量监控视频对视频编码提出了新的挑战。一方面，传统以预测/变换为核心的混合编码方法已经难以满足监控视频对高压缩率的需求。另一方面，视频监控系统中大量部署的是编码器，因此要求使用低复杂度的编码或转码算法实现监控视频实时存储或再压缩。
受模型编码方法的启发，本文致力于研究基于背景模型的高效监控视频编码算法，主要创新点包括：
第一，研究了复杂度低、高效率的背景建模和更新算法，用于显著去除监控视频中的背景冗余，适应低复杂度编码的需求。设计了基于背景模型的监控视频编码框架，证明了使用原始输入图像构建的背景模型可以获得更优的率失真结果。在此基础上，针对视频编码对背景模型的计算资源、存储资源和编码效率的要求，研究了两种低复杂度的背景模型，建立了场景内容和量化参数自适应的背景更新模型。与传统背景建模方法相比，两种背景模型分别在较低和最低复杂度下实现最优（平均1.19~1.23dB）和较优（平均0.91~0.99dB）的编码性能增益，所使用的背景更新模型可以进一步实现0.3~0.4dB的编码质量提升。此外，在极端环境视频上的实验也证明，所提出的模型对中等强度以上光照强度的各种天气条件都具有很好的适应能力。
第二，提出了一种基于背景差分预测的自适应运动补偿预测模型和编码算法，用于提高监控视频中前、背景像素混合数据块的预测效率，这是对传统编码框架的创造性扩展。从理论上分析证明了在背景差分编码下可以提高前、背景像素混合块编码效率的三个条件，设计了背景预测、短期预测和差分预测三种运动补偿的自适应选择机制和每种运动补偿下的编码模式选择算法，建立了基于背景差分预测的自适应运动补偿模型。与直接进行背景差分的编码方法相比，实现了18.45~31.75%的码率节省。与前景像素编码性能最优的长期参考关键帧编码方法相比，本模型在编码前景像素块时峰值信噪比提高了0.61~0.74dB。
第三，研究了一种基于背景预测的帧间层级编码优化算法，用于解决最新的HEVC和AVS2标准在监控视频编码时的压缩效率问题，同时还明显降低了编码复杂度，实效性和创新性强。通过比较现有的适用于低延迟监控视频编码的参考帧管理机制，分析了HEVC和AVS2层级编码方法能够提升性能的各原因，从实验和理论两方面论证了如何将建模背景与层级编码相结合以减少率失真代价。在此基础上，以提高编码效率为目标，提出了基于背景预测的分层参考帧选择和基于背景相似图像组检测的分级量化参数调整优化算法。以降低编码复杂度为目标，设计了基于编码单元分类的预测单元模式选择、编码单元划分和运动估计加速算法。针对监控视频和会议视频的实验表明，本算法与HEVC参考软件相比能够节省44.78%和13.79%的码率，而且能够把复杂度降低40%。
第四，设计了一种基于宏块分类的监控视频降码率转码算法，以很低的复杂度实现了转码效率的大幅度提高。该方法首先使用解码数据建立和编码背景图像，进而使用重建背景统计前景像素的分布情况，对待转码宏块进行分类。以此为基础，通过设计宏块类别自适应的转码模式选择、参考图像选择和运动估计精简算法，显著降低了转码过程中运动估计和模式选择的复杂度。实验表明该方法可以在H.264参考软件上实现60~80倍的全解全编转码速度提升。采用该算法，针对AVS和H.264标准设计实现的多路实时高清、超高清监控视频转码系统已被合作企业在产品中集成应用。
围绕上述算法，向国家数字音视频编解码技术标准工作组（简称AVS）提出的九项技术提案已被采纳并形成了AVS视频编码标准中的监控类标准，并且被批准为IEEE1857标准。与AVS国家标准的基准类和国际标准H.264相比，AVS监控类标准的编码效率提高了一倍。此外，还建立了监控视频测试码流库，生成了H.264和AVS监控类标准的编码位流，形成了用于对监控视频编码和分析算法进行评估的公开数据集。
In recent years, as the increasing requirements for emergency investigation, socialsecurity surveillance and smart video analysis, video surveillance systems are more andmore widely deployed in modern society. However, the long-time (months, even years)captured surveillance video also produces great challenges for video coding technology.On one hand, the tradional hybrid prediction/transform block based coding cannotsatisfy the requirement of high-efficiency surveillance video coding. On the other hand,there is much desire for low-complexity coding and transcoding algorithms to supportmultiple-path and real-time surveillance video coding. Inspired by recent developmentof model based coding and the characteristics of long-time static background ofsurveillance video, this paper engages to propose high-efficiency and low-complexitysurveillance coding algorithms based on novel low-computational-cost backgroundmodels.The main contributions can be summarized as follows:
1. In order to remove the background prediction redundancy, this paper proposesnovel background models and updating algorithms for high-efficiency surveillancevideo coding. Based on a theoretical analysis result that using background modeledfrom original input frames for background prediction can perform better video codingefficiency, this paper firstly makes an in-depth analysis of coding efficiency, time andmemory cost of multiple background models. Following these, two low-complexitybackground models are proposed for high-efficiency surveillance video coding. In themeantime, a scene-content and encoding-parameter adaptive background updatingmodel is proposed to tradeoff between reducing bit-cost of background coding and theprediction efficiency of input frames. Experiments show that, based on the proposedbackground model based framework, the novel background models can respectivelyachieve1.19~1.23dB and0.91~0.99dB gains respectively in relative low and lowestcomplexity, and the adaptive background updating model can further achieve0.3~0.4dBgains. Moreover, experiments on videos with kinds of complex environments prove that,our method can apply to different weather conditions with non-weak lightness.
2. To reduce the prediction redundancy of the blocks mixed with background andforeground pixels, this paper proposes coding unit adaptive motion compensationsbased on background difference prediction. For block-based hybrid coding, this paperfirstly proves that there is still room to improve the motion compensation efficiency forblocks mixed with background and foreground pixels theoretically. Furthermore, wederive three conditions when coding the current block in background difference domain,namely background difference motion compensation (BDMC), can significantlyimprove the coding efficiency. Based on the analyses above, we build up a backgroundbased adaptive motion compensation(MC) model, which adaptively selects short-termMC (traditional MC using recently decoded frames as reference), background referenceMC (with high-quality encoded and reconstructed background frame as long-termreference), and BDMC for different coding units. Moreover, a specially designed fastmode selection model is adopted to select different MCs for difference macroblockclassifications. Results show the method has18.45~31.75%total bit saving，0.61~0.74dB foreground gains.
3. To realize a further background redundancy reduction for the emerging videocoding standards HEVC and AVS2, this paper develops a hierarchical coding basedreference selection and bit-allocation optimization algorithm for HEVC and AVS2.Based on an analysis of their hierarchical coding structure in low-delay configurations,two components for efficiency improvement are concluded: hierarchical referenceselection and hierarchical quantization parameter (QP) decision. Inspired by this, weanalyze how to make use of the modeled background frame to optimize the emergingvideo coding standards’ coding efficiency for surveillance videos. Meanwhile, we alsosummarize how to optimize the QP relationships among frames and coding units forsurveillance videos. Following these conclusions, we assign different reference frameselection and QP calculation algorithms to improve the video coding efficiency fordifferent kinds of hierarchical prediction groups of frames. To reduce video codingcomplexity, we further employ a CU-classification based fast coding model to speed upsurveillance video coding. Extensive exepriments show that, this method respectivelyachieves44.8%and13.8%bit-saving for surveillance and conference videos, and thecomplexity reduction is more than40%.
4. In order to make the proposed surveillance video coding techniques moreapplicable, this paper proposes macroblock classification based transcoding methods forpractical surveillance video transcoding systems and presents the proposed surveillancevideo coding techniques for AVS surveillance group. In this paper, we propose to speedup the coding and transcoding procedure based on following model: classifying input coding units into three different categories and applying specially designed models ofmotion estimation simplification, reference frame selection and candidate predictionmode calcuation for each category. Results show the proposed method achieved60~80times speed up than the H.264/AVC reference model. Moreover, we also integrate thisalgorithm into real-time surveillance video coding and multiple-path paralleltranscoding systems for AVS and H.264video coding standard. The related encoder andtranscoder are adopted by some companies in their products. In addition, the relatedtechniques in this paper are proposed to AVS workgroup through tens of proposals. As aresult, AVS surveillance group can save half the bitrate of H.264/AVC and AVS+videocoding standard.
受模型编码方法的启发，本文致力于研究基于背景模型的高效监控视频编码算法，主要创新点包括：
第一，研究了复杂度低、高效率的背景建模和更新算法，用于显著去除监控视频中的背景冗余，适应低复杂度编码的需求。设计了基于背景模型的监控视频编码框架，证明了使用原始输入图像构建的背景模型可以获得更优的率失真结果。在此基础上，针对视频编码对背景模型的计算资源、存储资源和编码效率的要求，研究了两种低复杂度的背景模型，建立了场景内容和量化参数自适应的背景更新模型。与传统背景建模方法相比，两种背景模型分别在较低和最低复杂度下实现最优（平均1.19~1.23dB）和较优（平均0.91~0.99dB）的编码性能增益，所使用的背景更新模型可以进一步实现0.3~0.4dB的编码质量提升。此外，在极端环境视频上的实验也证明，所提出的模型对中等强度以上光照强度的各种天气条件都具有很好的适应能力。
第二，提出了一种基于背景差分预测的自适应运动补偿预测模型和编码算法，用于提高监控视频中前、背景像素混合数据块的预测效率，这是对传统编码框架的创造性扩展。从理论上分析证明了在背景差分编码下可以提高前、背景像素混合块编码效率的三个条件，设计了背景预测、短期预测和差分预测三种运动补偿的自适应选择机制和每种运动补偿下的编码模式选择算法，建立了基于背景差分预测的自适应运动补偿模型。与直接进行背景差分的编码方法相比，实现了18.45~31.75%的码率节省。与前景像素编码性能最优的长期参考关键帧编码方法相比，本模型在编码前景像素块时峰值信噪比提高了0.61~0.74dB。
第三，研究了一种基于背景预测的帧间层级编码优化算法，用于解决最新的HEVC和AVS2标准在监控视频编码时的压缩效率问题，同时还明显降低了编码复杂度，实效性和创新性强。通过比较现有的适用于低延迟监控视频编码的参考帧管理机制，分析了HEVC和AVS2层级编码方法能够提升性能的各原因，从实验和理论两方面论证了如何将建模背景与层级编码相结合以减少率失真代价。在此基础上，以提高编码效率为目标，提出了基于背景预测的分层参考帧选择和基于背景相似图像组检测的分级量化参数调整优化算法。以降低编码复杂度为目标，设计了基于编码单元分类的预测单元模式选择、编码单元划分和运动估计加速算法。针对监控视频和会议视频的实验表明，本算法与HEVC参考软件相比能够节省44.78%和13.79%的码率，而且能够把复杂度降低40%。
第四，设计了一种基于宏块分类的监控视频降码率转码算法，以很低的复杂度实现了转码效率的大幅度提高。该方法首先使用解码数据建立和编码背景图像，进而使用重建背景统计前景像素的分布情况，对待转码宏块进行分类。以此为基础，通过设计宏块类别自适应的转码模式选择、参考图像选择和运动估计精简算法，显著降低了转码过程中运动估计和模式选择的复杂度。实验表明该方法可以在H.264参考软件上实现60~80倍的全解全编转码速度提升。采用该算法，针对AVS和H.264标准设计实现的多路实时高清、超高清监控视频转码系统已被合作企业在产品中集成应用。
围绕上述算法，向国家数字音视频编解码技术标准工作组（简称AVS）提出的九项技术提案已被采纳并形成了AVS视频编码标准中的监控类标准，并且被批准为IEEE1857标准。与AVS国家标准的基准类和国际标准H.264相比，AVS监控类标准的编码效率提高了一倍。此外，还建立了监控视频测试码流库，生成了H.264和AVS监控类标准的编码位流，形成了用于对监控视频编码和分析算法进行评估的公开数据集。
In recent years, as the increasing requirements for emergency investigation, socialsecurity surveillance and smart video analysis, video surveillance systems are more andmore widely deployed in modern society. However, the long-time (months, even years)captured surveillance video also produces great challenges for video coding technology.On one hand, the tradional hybrid prediction/transform block based coding cannotsatisfy the requirement of high-efficiency surveillance video coding. On the other hand,there is much desire for low-complexity coding and transcoding algorithms to supportmultiple-path and real-time surveillance video coding. Inspired by recent developmentof model based coding and the characteristics of long-time static background ofsurveillance video, this paper engages to propose high-efficiency and low-complexitysurveillance coding algorithms based on novel low-computational-cost backgroundmodels.The main contributions can be summarized as follows:
1. In order to remove the background prediction redundancy, this paper proposesnovel background models and updating algorithms for high-efficiency surveillancevideo coding. Based on a theoretical analysis result that using background modeledfrom original input frames for background prediction can perform better video codingefficiency, this paper firstly makes an in-depth analysis of coding efficiency, time andmemory cost of multiple background models. Following these, two low-complexitybackground models are proposed for high-efficiency surveillance video coding. In themeantime, a scene-content and encoding-parameter adaptive background updatingmodel is proposed to tradeoff between reducing bit-cost of background coding and theprediction efficiency of input frames. Experiments show that, based on the proposedbackground model based framework, the novel background models can respectivelyachieve1.19~1.23dB and0.91~0.99dB gains respectively in relative low and lowestcomplexity, and the adaptive background updating model can further achieve0.3~0.4dBgains. Moreover, experiments on videos with kinds of complex environments prove that,our method can apply to different weather conditions with non-weak lightness.
2. To reduce the prediction redundancy of the blocks mixed with background andforeground pixels, this paper proposes coding unit adaptive motion compensationsbased on background difference prediction. For block-based hybrid coding, this paperfirstly proves that there is still room to improve the motion compensation efficiency forblocks mixed with background and foreground pixels theoretically. Furthermore, wederive three conditions when coding the current block in background difference domain,namely background difference motion compensation (BDMC), can significantlyimprove the coding efficiency. Based on the analyses above, we build up a backgroundbased adaptive motion compensation(MC) model, which adaptively selects short-termMC (traditional MC using recently decoded frames as reference), background referenceMC (with high-quality encoded and reconstructed background frame as long-termreference), and BDMC for different coding units. Moreover, a specially designed fastmode selection model is adopted to select different MCs for difference macroblockclassifications. Results show the method has18.45~31.75%total bit saving，0.61~0.74dB foreground gains.
3. To realize a further background redundancy reduction for the emerging videocoding standards HEVC and AVS2, this paper develops a hierarchical coding basedreference selection and bit-allocation optimization algorithm for HEVC and AVS2.Based on an analysis of their hierarchical coding structure in low-delay configurations,two components for efficiency improvement are concluded: hierarchical referenceselection and hierarchical quantization parameter (QP) decision. Inspired by this, weanalyze how to make use of the modeled background frame to optimize the emergingvideo coding standards’ coding efficiency for surveillance videos. Meanwhile, we alsosummarize how to optimize the QP relationships among frames and coding units forsurveillance videos. Following these conclusions, we assign different reference frameselection and QP calculation algorithms to improve the video coding efficiency fordifferent kinds of hierarchical prediction groups of frames. To reduce video codingcomplexity, we further employ a CU-classification based fast coding model to speed upsurveillance video coding. Extensive exepriments show that, this method respectivelyachieves44.8%and13.8%bit-saving for surveillance and conference videos, and thecomplexity reduction is more than40%.
4. In order to make the proposed surveillance video coding techniques moreapplicable, this paper proposes macroblock classification based transcoding methods forpractical surveillance video transcoding systems and presents the proposed surveillancevideo coding techniques for AVS surveillance group. In this paper, we propose to speedup the coding and transcoding procedure based on following model: classifying input coding units into three different categories and applying specially designed models ofmotion estimation simplification, reference frame selection and candidate predictionmode calcuation for each category. Results show the proposed method achieved60~80times speed up than the H.264/AVC reference model. Moreover, we also integrate thisalgorithm into real-time surveillance video coding and multiple-path paralleltranscoding systems for AVS and H.264video coding standard. The related encoder andtranscoder are adopted by some companies in their products. In addition, the relatedtechniques in this paper are proposed to AVS workgroup through tens of proposals. As aresult, AVS surveillance group can save half the bitrate of H.264/AVC and AVS+videocoding standard.
引文
[1]高文，赵德斌，马思伟，“数字视频编码技术原理”北京：科学出版社，2010
[2] MPEG.“Coding of moving pictures and associated audio—for digital storage media at up toabout1.5Mbit/s—Part2: Video,” ISO/IEC11172-2(MPEG-1),1993.
[3] ITU-T.“Video codec for audio sisual services at px64kbit/s,” in ITU-T Recommendation H.261,1993.
[4] ITU-T.“Information technology—generic coding of moving pictures and associated audioinformation: video,” in ITU-T Recommendation H.262|ISO/IEC13818-2(MPEG-2),1995.
[5] ITU-T.“Video coding for low bitrate communication,” ITU-T Recommendation H.263,1998.
[6] ITU-T.“Advanced video coding for generic audio visual services,” in ITU-T Rec.H.264andISO/IEC14496-10(MPEG-4AVC), ITU-T and ISO/IEC JTC1, version1, May2003.
[7] AVS Workgroup.“Information technology—advanced coding of audio and video—Part2: video,”in AVS1-P2,2005.
[8] B. Bross, W. J. Han, G. J. Sullivan, J. R. Ohm and T. Wiegand,“Text of ISO/IEC DIS23008-2High Efficiency Video Coding,” in document JCTVC-N12935, Stockholm, Sweden, July2012.
[9] S. Ma and C. C. Kuo,“High-definition video coding with super-macroblocks,” in Proc. SPIEVisual Commun. Image Process., vol.6508,2007.
[10] Il-Koo Kim, Ken McCann, Kazuo Sugimoto and et al.,“HM9: High Efficiency Video Coding(HEVC) Test Model9Encoder Description,” JCTVC-N12935, Shanghai, Oct.2012.
[11] J.-H. Min, S. Lee, I. K. Kim, W. J. Han, J. Lainema and K. Ugur,“Unification of the DirectionalIntra Prediction Methods in TMuC,” JCTVC-B100, Geneva, Switzerland, Jul2010.
[12] TK Tan and Frank Bossen,“TE5: Results for Simplification of Unified Intra Prediction,”JCTVC-C042, Guangzhou, China, Oct2010.
[13] J. Chen, V. Seregin, S. Lee, W. Han, J. Kim, B.M. Jeon,“CE6.a.4: Chroma intra prediction byreconstructed luma samples,” JCTVC-E266, Geneva, CH, March2011.
[14] Sandeep Kanumuri and Frank Bossen,“CE6.e/f: Planar mode experiments and results,” indocument JCTVC-E321, Geneva, CH, March2011.
[15] K. R. Rao and P. Yip,“Discrete Cosine Transform: Algorithms, Advantages, Applications,” SanDiego, CA: Academic,1990.
[16] W. K. Pratt, J. Kane and H. C. Andrews,“Hadamard transform image coding,” in Proceeding ofthe IEEE, vol.57, Jan.1969, pp.58-68.
[17] K. Karhunen and Kari,“über Lineare Methoden in der Wahrscheinlichkeitsrechnung,” in Ann.Acad. Sci. Fennicae. Ser. A. I. Math.-Phys., no.37,1947, pp.1-79.
[18] R. M. Gray and D. L. Neuhoff,“Quantization,” IEEE Transactions on Information Theory,” vol.44, May1977, pp.2325-2383.
[19] J. Rissanen and G. G. Langdon,“Arithmetic coding,” IBM Journal of Research andDevelopment, vol.23,1979, pp.149-162.
[20] H C Andrews and W K Pratt,“Fourier Transform Coding of Images,” Hawaii Intl. Conf. onSystem Sciences, Sep1967.
[21] B. Bross H., Kirchhoffer, H. Schwarz and T. Wiegand,“Fast intra encoding for fixed maximumdepth of transform quadtree” JCTVC-C311, Guangzhou, China, Oct2010.
[22] T. Wiegand, H. Schwarz, B. Bross H., Kirchhoffer, X. Wang and A. Fuldseth,“BoG report:residual quadtree structure” JCTVC-C319, Guangzhou, China, Oct2010.
[23] I.-K Kim, W.-J Han, J. H. Park and X. Zheng,“CE2: Test results of asymmetric motionpartition (AMP),” in document JCTVC-F379, July2011.
[24] S. F. Chang, W. L. Chen and D.G. Messerschmitt,“Video Compositing in the DCT Domain,” inIEEE Workshop on Visual Signal Processing and Communications, pp.138-143,1992.
[25] Andrei Sharf, Marc Alexa and Daniel Cohen-Or.“Context-based surface completion,” ACMTransactions on Graphics, vol.23(3),878-887,2004.
[26] Y. Ye and M. Karczewicz,“Improved H.264Intra coding based on bi-directional Intraprediction, directional transform and adaptive coefficient scanning,” in IEEE InternationalConference on Image Processing (ICIP), pp.2116-2119, Oct.2008.
[27] Y. Su and M. Sun,"Fast Multiple Reference Frame Motion Estimation for H.264/AVC," inIEEE Trans. Circuits Syst. Video Technol., vol.16(3), pp.447-452, Mar.2006.
[28] R. Sj berg, D. Flynn, Y. Chen, Y. K. Wang, TK Tan and W. K. Wan,“JCT-VC AHG report:Reference picture buffering and list construction (AHG21),” JCT-VC Document, JCTVC-G021,Geneva, Switzerland, November2011.
[29] Y. Chen, C. Muhammed, W. Chien and et al.,“Comments on Generalized P and B Pictures,”JCTVC-D401, Daegu, KR, Jan.2011.
[30] Y Ye and Y. He,“AHG21: Reference picture lists combination syntax,” JCTVC-H0137, SanJosé, CA, USA, February2012.
[31]A.Fujibayashi and F.Bossen,“CE93.2d Simplified Motion vector prediction,” JCTVC-D231,Daegu Korea, Jan.2011
[32] E. Alshina, J. Chen, E. Alshin, N. Shlyakhov and W.-J. Han,“Experimental results of DCT-IFby samsung," JCTVC-D344, Daegu Korea, Jan.2011.
[33] J. Chen, E. Alshina and W.-J. Han,"Experimental results of DCTIF application for Chroma MCby Samsung", JCTVC-D347, Daegu Korea, Jan.2011.
[34] T. Chujoh and R. Noda,“Internal bit depth increase except frame memory,” ITU-T SG16Q.6Document, VCEG-AF07,32nd VCEG Meeting, San Jose, USA, April2007.
[35] K. Ugur, J. Lainema and A. Hallapuro,“High precision bi-directional averaging,” JCTVC-D321,Daegu Korea, Jan.2011.
[36] Y. Huang, B. Bross, M. Zhou and et al.“CE9：Summary report of core experiment on MVcoding and skip/merge operations,” JCTVC-F029, Torino, IT, Jul.2011.
[37] A. Saxena and F. Fernandes,“CE7: Mode-dependent DCT/DST for intra prediction in videocoding,” JCTVC-D033, Daegu, Korea, Jan.2011.
[38] Ankur Saxena and Felix C. Fernandes,“CE7: Mode-dependent DCT/DST without4×4fullmatrix multiplication for intra prediction”, JCTVC-E125, Geneva, CH, March2011.
[39] C. Fu, C. Chen, Y. Huang and et al.“CE10subtest3: Quadtree-based adaptive offset,”JCTVC-C147,2010.
[40] Y. Zheng, M. Coban and M. Karczewicz “CE13: Mode Dependent Hybrid Intra Smoothing,”JCTVC-D282, Daegu, Jan.2011.
[41] Y. Zheng, M. Coban, X. Wang, J. Sole, R. Joshi and M. Karczewicz,“CE11: Mode DependentCoefficient Scanning”, Doc. JCTVC-D393, Daegu, KR, Jan.2011.
[42] G. Bj ntegaard and K. Lillevold,“Context-adaptive VLC (CVLC) coding of coefficients,”JVT-C028,3rd Meeting: Fairfax, Virginia, USA,6-10May2002.
[43] Q. Wang, D. Zhao and W. Gao,“Context-Based2D-VLC Entropy Coder in AVS Video CodingStandard,” in Journal of Computer Science&Technology. vol.21(3), pp.315-322, May2006
[44] D. Marpe, H. Schwarz and T. Wiegand,“Context-Based Adaptive Binary Arithmetic Coding inthe H.264/AVC Video Compression Standard,” IEEE Trans. on Circuits and Systems for VideoTechnology, vol.13, issue.7, pp.620-636,2003.
[45] M. Budagavi, V. Sze, M. Demircin and et al.“Video coding technology proposal by TexasInstruments,” JCTVC-A101, Desden, April2010.
[46] R. Forchheimer and O. Fahlander,“Low bit-rate coding through animation,” in Proc. Int.Picture Coding Symp.(PCS), Davis, CA, pp.113-114,1983.
[47] R. Forchheimer, O. Fahlander and T. Kronander,“A semantic approach to the transmission offace images,” in Proc. Int. Picture Coding Symp., Cesson-Sevigne, France,1984.
[48] W. J. Welsh,“Model-based coding of moving images at very low bit rates,” in Proc. Int. PictureCoding Symp., Stockholm, Sweden,1987.
[49] K. Aizawa,“Model-based analysis-synthesis image coding system for very low-rate imagetransmission,” in Proc. Int. Picture Coding Symp., Turin, Italy,1988.
[50] K. Aizawa, H. Harashima and T. Saito,“Model-based analysis-synthesis image coding(MBASIC) for a person’s face,” in Image Commun., vol.1(2), pp139-152,1989.
[51] H. G. Musmann, M. Hotter and J. Ostermann,“Object-oriented analysis-synthesis of movingimages,” in Image Commun., vol.1(2), pp.117-138,1989.
[52] J. Y. Wang and E. H. Adelson “Representing moving images with layers,” in IEEE Trans. ImageProcess., vol.3(5), pp.625-638,1994.
[53] D. Chai and K. Ngan,“Foreground/background video coding scheme,” in Proc. IEEE Int. Symp.Circuits Syst., Hong Kong, vol.2, pp.1448-1451, June,1997.
[54] I. Martins and L. Corte-Real,“A video coder using3-D model based background for videosurveillance applications,” in Proc. IEEE Int. Conf. Image Process., pp.919-923,1998.
[55] I. E. G. Richardson,“H.264and MPEG-4video compression: video coding for next generationmultimedia,” in John Wiley&Sons Ltd, Chichester, England, pp.136-138,2003.
[56] K. Toyama, J. Krumm, B. Brumitt and B. Meyers,“Wallflower: principles and practice ofbackground maintenance,” in Proc. Int. Conf. Computer Vision, pp.255-261,1999.
[57] I. Haritaoglu, D. Harwood and L. Davis,“W4: real-time surveillance of people and theiractivities,” in IEEE Trans. Pattern Anal. Mach. Intell., vol.22(8),809-830,2000.
[58] A. Elgammal,“Efficient nonparametric kernel density estimation for real time computer vision,”in Ph.D. Thesis, Rutgers, the State University of New Jersey,2002.
[59] A. Elgammal, D. Harwood and L. Davis,“Non-parametric model for background subtraction,”in Proc. Sixth European Conf. Computer Vision, vol.2, pp.751-767,2000.
[60] Y. Heikh and M. Shah,“Bayesian modeling of dynamic scenes for object detection,” in IEEETrans. Pattern Anal. Mach. Intell., vol.27(11), pp.1778-1792,2005.
[61]L. Cheng, M. Gong, D. Schuurmans and T. Caelli,“Real-time discriminative backgroundsubtraction,” in IEEE Trans. Image Process., vol.20(5), pp.1401-1414,2011.
[62] J. K. Suhr, H. G. Jung, G. Li and et al.“Mixture of Gaussians-based Background Subtractionfor Bayer-Pattern Image Sequences,” in IEEE Trans. Circuits Syst. Video Technol., vol.21(3),pp.365-370,2010.
[63] J. Ding, M. Li, K. Huang and T. Tan,“Modeling complex scenes for accurate moving objectssegmentation,” in Proc. Tenth Asian Conf. Computer Vision, pp.592-604,2010.
[64] E. Francois, J.-F. Vial and B. Chupeau,“Coding algorithm with region-based motioncompensation,” in IEEE Trans. Circuits Syst. Video Technol. vol.7(1), pp.97-108,1997.
[65] A. Vetro, T. Haga, K. Sumi and et al.,“Object-based coding for long-term archive ofsurveillance video,” in Proc. IEEE Int. Conf. Multimedia and Expo, pp.417-420,2003.
[66] R.V. Babu and A. Makur,“Object-based surveillance video compression using foregroundmotion compensation,” in Int. Conf. Control, Automatic, Robotics and Vision,2006.
[67] A. Hakeem, K. Shafique and M. Shah,“An object-based video coding framework for videosequences obtained from static cameras,” in Proc. ACM Int. Conf. on Multimedia, pp.608-617,2005.
[68] D. Venkatraman and A. Makur,“A compressive sensing approach to object-based surveillancevideo coding,” in IEEE Int. conf. Acoustics, Speech, Signal Process., pp.3513-3516, Apr.2009.
[69] X. Jin and S. Goto,“Encoder adaptable difference detection for low power video compressionin surveillance system,” in Sig. Proc.: Image Comm., vol.26(3), pp.130-142,2011.
[70] T. C. Chen, Y. W. Huang, C. Y. Tsai, C. T. Huang and L. G. Chen,"Single reference framemultiple current macroblocks scheme for multi-frame motion estimation in H.264/AVC", inProc. IEEE Int. Symp. Circuits Syst., vol.2, pp.1790-1793,2005.
[71] R. Ding, Q. Dai, W. Xu, D. Zhu and H. Yin,"Background-frame based motion compensationfor video com-pression," in Proc. IEEE Int. Conf. Multimedia and Expo,2004
[72] M. Paul, W. Lin, C. T. Lau and B. S. Lee,"Video coding using the most common frame inscene," in Interna-tional conference on Acoustics, Speech and Signal processing, pp.734-737,2010
[73] X. Zhang, L. Liang, Q. Huang and W. Gao,"An efficient coding scheme for surveillance videoscaptured by stationary cameras," in Proc. Visual Commun. Image Process., July2010
[74] M. Paul, W. Lin, C. T. Lau and B. S. Lee,"Explore and model better I-frame for video coding,"in IEEE Transactions on Circuits and Systems for Video Technology, vol.21(9), pp.1242-1254,2011.
[75] B. P. L. Lo and S. A. Velastin,“Automatic congestion detection system for undergroundplatforms,” in Proc. ISIMP2001, pp.158-161, May2001.
[76] R. Cucchiara, C. Grana, M. Piccardi and A. Prati,“Detecting moving objects, ghosts, andshadows in video streams,” in IEEE Trans. on Patten Anal. and Machine Inteli., vol.25(10), pp.1337-1442,2003
[77] M. Piccardi,“Background subtraction techniques: a review,” in Proc. IEEE Man andCybernetics,2004.
[78] A. Elgammal, D. Hanvood and L.S. Davis,“Nonparametric model for background subtraction,”in Proc. ECCV2000, pp.751-767, Jun.2000
[79] N.M. Oliver, B. Rosario and A.P. Pentland,“A Bayesian computer vision system for modelinghuman interactions,” in IEEE Trans. on Paftern Anal. and Machine Intell., vol.22(8), pp.831-843,2000.
[80] K. Fukunaga,“The Estimation of the Gradient of a Density Function with Applications inPattern Recognition,” in IEEE Transactions on Information Theory, vol.4(2), pp.32-40,1975
[81] C. Wren, A. Azarhayejani, T. Darrell and A.P. Pentland,“Pfinder: real-time tracking of thehuman body,” in IEEE Trans. on Pattern Anal. and Machine Intell., vol.19(7), pp.780-785,1997
[82] M. Haque, M. Murshed and M. Paul,“Improved Gaussian mix-tures for robust object detectionby adaptive multi-background generation,” in IEEE Conf. on Computer Vision and PatternRecognition,2008.
[83] K. Kim, T. H. Chalidabhongse, D. Harwood and et al.“Real-time foreground-backgroundsegmentation using codebook model,” in Real-time imaging, vol.20(11), pp.172-185,2005.
[84] B. Girod,“The Efficiency of Motion-compensating Prediction for Hybrid Coding of VideoSequences,” in IEEE J. Selecl. Areas Commun., vol.5(8), pp.1140-1154,1987.
[85] B. Girod,“Efficiency Analysis of Multihypothesis Motion-compensated Prediction for VideoCoding,” in IEEE Transaction on Image Process., vol.9(2), pp.173-183,2000.
[86] N. S. Jayant and P. Noll,“Digital Coding of Waveforms. Englewood Cliffs,” in NJ:Prentice-Hall,1984.
[87] F. Pan, X. Lin, R. Susanto, K. P. Lim, Z. G. Li, G. N. Feng, D. J. Wu and S. Wu,“Fast modedecision algorithm for intraprediction in H.264/AVC Video Coding,” in IEEE Trans. CircuitsSyst. Video Technol., vol.15, pp.813-822, Jul.2005.
[88] D. Wu, F. Pan, K. P. Lim, S. Wu, Z. G. Li, X. Lin, R. Susanto and C. C. Kuo,“Fast inter modedecision in H.264/AVC Video Coding,” in IEEE Trans. Circuits Syst. Video Technol., vol.15,pp.953-958, Jul.2005.
[89] G. J. Sullivan and T. Wiegand,“Rate-distortion optimization for video compression,” in IEEESignal Processing Magazine, vol.15, pp.74-90, Nov.1998.
[90] Y. K. Tu, J. F. Yang and M. T. Sun,“Efficient rate-distortion estimation for H264/AVC coders,”in IEEE Trans. Circuits Syst. Video Technol., vol.16, pp.600-611, May2006.
[91] M. G. Sarwer and L. M. Po,“Fast bit rate estimation for mode decision of H.264/AVC,” inIEEE Trans. Circuits Syst. Video Technol., vol.17, pp.1402-1407, Oct.2007.
[92] Y. K. Tu, J. F. Yang and M. T. Sun,“Rate-Distortion Modeling for Efficient H.264/AVCEncoding,” in IEEE Trans. Circuits Syst. Video Technol., vol.17, pp.530-543, May2007,
[93] C. C. Chen, C. O. T. C and H. H. Wu,“Region of Interest Determined by Picture Contents inJPEG2000,” in IEEE International Symposium on Circuits and Systems, vol.2, pp.868-871,2003.
[94] D. Nistr, C. Christopoulos,“Lossless Region of Interest Coding,” in Signal Processing, vol.78,pp.1-17,1999.
[95] D. N., D. A. and K. D.,“Low Bit-rate Coding of Image Sequences Using Adaptive Regions ofInterest,” in IEEE Transaction On Circuits and Systems for Video Technology, vol.8(8), pp.928-934,1998.
[96] M. M. and M. K., F. K.“A Hierarehical Video Compression Method Using Object Coding,” inProceedings of world Automation Congress, vol12, pp.345-350,2002.
[97] M. M., Hannuksela, Y. kui Wang and et al.“Sub-picture: Roi Coding and UnequalErrorProtection,” in IEEE International Conference on Image Processing. Rochester, New York,USA,537-540,2002.
[98] Y. Liu, Z. G. Li and Y. C. Soh,“Region-of-interest Based Resource Allocation forConversational Video Communication of H.264/AVC,” in IEEE Transaction On Circuits andSystems for Video Technology, vol18(1), pp.134-139,2008.
[99] Y. Liu, Z. G. Li and Y. C. Soh,“A Novel Rate Control Scheme for Low Delay VideoCommunication of H.264/AVC Standard,” in IEEE Transaction On Circuits and Systems forVideo Technology, vol.17(1),2007.
[100] R. K., O. A. and V. M.,“Bit Allocation for Dependent Quantization with Applications toMultiresolution and Mpeg Video Coders,” in IEEE Trans. Signal Processing, vol.3(5), pp.533-545,1994.
[101] J. R. Ding and J. F. Yang,“Adaptive group-of-pictures and scene change detection methodsbased on existing H.264advanced video coding information,” in IET Image Processing, vol2(2), pp.85-94,2008.
[102] T. Wiegand, X. Zhang and B. Girod,“Long-term memory motion-compensated prediction,” inIEEE Trans. Circuits Syst. Video Technol., vol.9(1), pp.70-84,1999.
[103]M. Tiwari, P.C. Cosman,“Selection of long-term reference frames in dual-frame video codingusing simulated annealing,” in IEEE Signal Processing Letters, vol.15, pp.249-252,2008.
[104] D. Liu, D. Zhao, X. Ji and et al.,“Dual frame motion compensation with optimal long-termreference frame selection and bit allocation,” in IEEE Trans. Circuits Syst. Video Technol., vol.20(3), pp.325-339, Mar.2010.
[105] A. Leontaris and P. C. Cosman,“Compression efficiency and delay tradeoffs for hierarchicalB-picture frames and pulsed-quality frames,” in IEEE Trans. Image Process., vol.16(7), pp.1726-1740, Jul.2007.
[106] H. Schwarz, D. Marpe and T. Wiegand,“Overview of the Scalable Video Coding Extension ofthe H.264/AVC Standard,” in IEEE Trans. Circuits Syst. Video Technol., vol.17(9), pp.1103-1120, Sep.2007.
[107] J. Xu, F. Wu and H. Li,“Encoding optimization to improve coding efficiency for low delaycases,” in JCT-VC document JCTVC-F701r1, Jul.2011.
[108] Frank Bossen,“HM8Common Test Conditions and Software Reference Configurations,” inJCT-VC document JCTVC-J1100, Jul.2012.
[109]G. Bjontegaard,“Calculation of average PSNR difference between RD-curves,” in documentVCEG-M33.doc, ITU-T VCEG,13th Meeting, Austin, TX, Apr.2001.
[110] A. Vetro, C. Christopoulos and H. Sun,“Video transcoding architectures and techniques: anoverview,” in IEEE Signal Processing Magazine, vol.20(2), pp.18-29, March2003.
[111] H. Sun, W. Kwok and J. W. Zdepski,“Architectures for mpeg compressed bitstream scaling,”in IEEE Transactions on Circuits and Systems for Video Technology, vol.6(2), pp.191-199,April1996.
[112] P. A. A. Assuncao and M. Ghanbari,“A frequency-domain video transcoder for dynamicbit-rate reduction of mpeg-2bit streams,” in IEEE Transactions on Circuits and Systems forVideo Technology, vol.8(8), pp.953-967, Dec1998.
[113] G. J. Shen, Y. He, W. Cao and S. Li,“MPEG-2to WMV transcoder with adaptive errorcompensation and dynamic switches,” in IEEE Transactions on Circuits and Systems for VideoTechnology, vol.16(12), pp.1460-1476, November2006.
[114] L. Yuan, F. Wu, Q. Chen, S. Li and W. Gao,“The fast close-loop video transcoder with limiteddrifting error,” in IEEE International Symposium on Circuits and Systems, pp.769-772, vol.3,Mar.2004.
[115]袁禄军，视频转码技术的研究及其应用，（博士论文）2005
[116] J. Xin, C. W. Lin and M. T. Sun,“Digital video transcoding,” in Proceeding of the IEEE, vol.93(1), pp.84-97, Jan.2005.
[117] T. Shanableh,“Hybrid dct/pixel domain architecture for heterogeneous video transcoding,” inSignal Processing: Image Communication, vol.18(8), pp.601-620, Sept.2003.
[118] H. Schwarz, D. Marpe and T. Wiegand,“Overview of the scalable video coding extension ofthe H.264standard,” in IEEE Transactions on Circuits and Systems for Video Technology, vol.17(9), pp.1103-1120, September2007.
[119] Y. Liang and Y.-P. Tan,“Methods and needs for transcoding mpeg-4fine granularity scalabilityvideo,” in IEEE International Symposium on Circuits and Systems, pp.719-722,2002.
[120] H. Sun, T. Chiang and X. Chen,“Digital video transcoding for transmission and storage,” inCRC Press, May2004.
[122] J. Youn, M.T. Sun and C.W. Lin,“Motion vector refinement for high performance transcoding,”in IEEE Trans. Multimedia, vol.1, pp.30-40, Mar.1999.
[123] Y. Shin, N. Son, N. D. Toan and G. Lee,“Low-complexity heterogeneous video transcoding bymotion vector clustering,” in Information Science and Applications,2010.
[124] K. T. Fung and W. C. Siu,“Low complexity H.263to H.264video transcoding using motionvector decomposition,” in IEEE Int. Symp. Circuits Syst.,2005.
[125] H. Kalva and P. Kunselmann,“Dynamic motion estimation for transcoding P frames in H.264to MPEG-2transcoders,” in IEEE T. Consum. Electr., vol.54, pp.657-661,2008.
[126] C. D. Wu and Y. Lin,“Efficient inter/intra mode decision for H.264/AVC inter frametranscoding” in Proc. IEEE Int. Conf. Image Process.,2009.
[127] P. Zhang, Q. M. Huang and W. Gao,“Key techniques of bit-rate reduction for H.264streams,”in Proc. Pacific-Rim Conf. Multimedia,2004.
[128] X. Lu, A. M. Tourapis, P. Yin and J. Boyce,“Fast mode decision and motion estimation forH.264with a focus on MPEG-2/H.264transcoding,” in IEEE Int. Symp. Circuits Syst.,2005.
[129] A. Vetro, H. Sun and Y. Wang,“Object-based transcoding for scalable quality of service,” inIEEE Int. Symp. Circuits and Systems,2000.
[130] T. Hata, N. Kuwahara, T. Nozawa and et al.“Surveillance system with object-aware videotranscoder,” in IEEE Int. Workshop on Multimedia Sig. Process.,2005
[131] D. Kubasov,“Mesh-based motion-compensated interpolation for side information extraction indistributed video coding,” in IEEE International Conference on Image Processing, pp.261-264,2006.
[132] A. Smolic, K. Mueller, N. Stefanoski, J. Ostermann, A. Gotchev, G. B. Akar, G. Triantafyllidisand A. Koz,“Coding algorithms for3DTV—a survey,” in IEEE Transactions on Circuits andSystems for Video Technology, vol.17(11), pp.1606-1621, Nov.2007.
[133] T. Sikora,“Trends and perspectives in image and video coding,” in Proceeding of the IEEE,vol.93(1), pp.6-17, Jan.2005.
[134] M. Kunt, A. Ikonomopoulos and M. Kocher,“Second-generation image-coding techniques,” inProceeding of the IEEE, vol.73(4), pp.549-574, Apr.1985.
[135] M. Civanlar, S. Rajala and W. Lee,“Second generation hybrid image-coding techniques,” inProceedings of SPIE Visual Communications and Image Processing, vol.707, pp.132-137,1986.
[136] X. Zhang, L. Liang, Q. Huang, Y. Liu, T. Huang and W. Gao,“An efficient coding scheme forsurveillance videos captured by stationary cameras,” in Proceedings of SPIE Conference onVisual Communications and Image Processing, vol.7744, pp.77442A-1-10,2010.
[137] H. Yue, X. Sun, F. Wu and J. Yang,“SIFT-based Image Compression,” in IEEE InternationalConference on Multimedia and Expo, pp.473-478,2012.
[138] P. Ndjiki-Nya, D. Doshkov, H. Kaprykowsky, F. Zhang, D. Bull and T. Wiegand,“Perception-oriented video coding based on image analysis and completion: A review,” inSignal Processing: Image Communication, vol.27(6), pp.579-594, Feb.2012.
[139] S. Wang, J. Fu, Y. Lu, S. Li and W. Gao,“Content-Aware Layered Compound VideoCompression,” in IEEE International Symposium on Circuits and Systems, pp.145-148,2012.
[140] H. Harashima, K. Aizawa and T. Saito,“Model based analysis synthesis coding ofvideotelephone images—conception and basic study of intelligent image coding,” inTransactions IEICE, vol. E72(5), pp.452-458, May1989.
[141] P. Cicconi, E. Reusens, F. Dufaux, I. Moccagatta, B. Rouchouze, T. Ebrahimi and M. Kunt,“New trends in image data compression,” in Computerized Medical Imaging and GraphicsJournal, vol.18(2), pp.107-124, Mar.1994.
[142] H. Li, A. Lundmark and R. Forchheimer,“Image sequence coding at very low bit rates: areview,” in IEEE Transactions on Image Processing, vol.3(5), pp.589-609, Sept.1994.
[143] D. E. Pearson,“Developments in model based video coding,” in Proceedings of the IEEE, vol.83(6), pp.892-906, June1995.
[144] K. Aizawa and T. Huang,“Model-based Image coding: advanced video coding Techniques forVery Low Bit-Rate Applications,” in Proceeding of the IEEE, vol.83(2), Feb.1995.
[145] B. Girod, K. Younes, R. Bernstein, P. Eisert, N. Farber, F. Hartung, U. Horn, E. Steinbach, K.Stuhlmuller and T. Wiegand,“Recent advances in video compression,” in IEEE InternationalSymposium on Circuits and Systems, vol.2, pp.580-583,1996.
[146] F. Pereira, Shih-fu Chang, R. Koenen, A. Puri and O. Avaro,“Introduction to the special issueon object-based video coding and description,” in IEEE Transaction on Circuits and Systemsfor Video Technology, vol.9(8), pp.1144-1146, Dec.1999.
[147] T. Sikora,“Trends and perspectives in image and video coding,” in Proceeding of the IEEE,vol.93(1), pp.6-17, Jan.2005.
[148] W. F. Schreiber, C. F. Knapp and N. D. Kay,“Synthetic highs—an experimental TV bandwidtheducation system,” in Journal of Society of Motion Picture and Television Engineers, vol.68,pp.525-537, Aug.1959.
[149] Musmann,“Source models for image sequence coding,” in Int. Workshop on Coding Techn.for Very Low Bit-rate video, University of Essex, UK, Apr.1994.
[150] V. Seferidis and M. Ghanbari,“General approach to block-matching motion estimation,” inOptical Engineering, vol.32(7), pp.1464-1474, Jul.1993.
[151] G. J. Sullivan and R. L. Baker,“Motion compensation for video compression using controlgrid interpolation,” in IEEE International Conference on Acoustics, Speech and SignalProcessing, pp.2713-2716,1996.
[152] H. Brusewitz,“Motion compensation with triangles,” in Proc.3rd International workshop on64k bits/s Coding of Moving Video, Sept.1990.
[153] O. D. Escoda, P. Yin, C. Dai and X. Li,“Geometric-adaptive bock partitioning for videocoding,” in IEEE International Conference on Acoustics, Speech and Signal Processing, vol.1,pp.657-660,2007.
[154] L. Guo, P. Yin and E. Francois,“TE:3simplified geometry block partitioning,” in documentJCTVC-B085, Geneva, Switzerland, Jul2010.
[155] D. Graham,“Image transmission by two-dimensional contour coding,” in Proceeding of theIEEE, vol.55(3), pp.336-346, Mar.1967.
[156] M. J. Biggar, O.J. Morris and A.G. Constantinides,“Segmented image coding: performancecomparison with the discrete cosine transform,” in IEE Proceedings, Part F, vol.135(2), pp.121-132, Apr.1988.
[157] M. Gilge, T. Engelhardt and R. Mehlan,“Coding of Arbitrarily Shaped Image Segments Basedon A Generalized Orthogonal Transform,” in Signal Processing: Image Communication, vol.1(2), pp.153-180, Oct.1989.
[158] P. Willemin, T. Reed and M. Kunt,“Image sequence coding by split and merge,” in IEEETransactions on Communications, vol.39(12), pp.1845-1855,1991.
[159] W. Li and M. Kunt,“Morphological segmentation applied to displaced frame differencecoding,” in Signal Processing, vol.38(1), pp.45-56, July1994.
[160] P. Salembier, L. Torres, F. Meyer and C. Gu,“Region-based video coding using mathematicalmorphology,” in Proceeding of the IEEE vol.83(6), pp.843-857, Jun.1995.
[161] F. Marqu′es, V. Vera and A. Gasull,“A hierarchical image sequence model for segmentation:application to object-based sequence coding,” in Proceedings of SPIE Visual Communicationsand Signal Processing, pp.554-563, Oct.1994.
[162] C. Gu and M. Kunt,“Very low bit-rate video coding using multi-criterion segmentation,” inIEEE International Conference on Image Processing, vol. II, pp.418-422, Nov.1994.
[163] H. G. Musmann, M. Hotter and J. Ostermann.“Object oriented analysis-synthesis coding ofmoving images,” in Singnal Procesing: Image communications, vol.1(2), pp.117-138, Oct.1989.
[164] P. Salembier, F. Marqu′es, M. Pard`as and et al.,“Segmentation-based video coding systemallowing the manipulation of objects,” in IEEE Transactions on Circuits and Systems for VideoTechnology, vol.7(1), Feb.1997.
[165] F. Parke,“Parameterized models for facial animation,” in IEEE Comput. Graph. Applicat.Mag., vol.12, pp.61-68, Nov.1982.
[166] R. Forchheimer, O. Fahlander and T. Kronander,“A semantic approach to the transmission offace images,” in International Picture Coding Symposium,1984.
[167] C. F. Hall,“Digital color image compression in a perceptual space,” in Doctoral Dissertation,University of Southern California Los Angeles, CA, USA,1978
[168] D. J. Sakrison,“Image coding applications of vision models,” in In: W. K. Pratt (Ed.), ImageProcessing Techniques, Academic Press, San Diego, CA pp.21-71,1979.
[169] Y. Li, X. Sun, H. Xiong and F. Wu,“Incorporating Primal Sketch Based Learning Into LowBit-Rate Image Compression,” in Proceedings of International Conference on Image Processing,vol.3, pp.173-176,2007.
[170] X. Sun and F. Wu,“Classified patch learning for spatially scalable video coding,” in IEEEInternational Conference on Image Processing, pp.2301-2304,2009.
[171] Y. Yang, O. C. Au, L. Fang, X. Wen and W. Tang.“Perceptual compressive sensing for imagesignals,” in IEEE International Conference on Multimedia and Expo, pp.89-92, June2009.
[172] M. R. Pickering, J. You, T. Ebrahimi and A. Perkis.“A compressive sensing approach toperceptual image coding,” in Proceedings of SPIE Applications of Digital Image ProcessingXXXIII, vol.7798, pp.77981E-1-11,2010.
[173] D. Kubasov,“Mesh-based motion-compensated interpolation for side information extraction indistributed video coding,” in IEEE International Conference on Image Processing, pp.261-264,2006.
[174] A. Smolic, K. Mueller, N. Stefanoski, J. Ostermann, A. Gotchev, G. B. Akar, G. Triantafyllidisand A. Koz,“Coding algorithms for3DTV—a survey,” in IEEE Transactions on Circuits andSystems for Video Technology, vol.17(11), pp.1606-1621, Nov.2007.
[175] L. C. Wilkins and P. A. Wintz,“Studies on data compression: part1: picture coding bycontours,” in Purdue University, School of Electronic Engineering, Tech. Report70-17, Sept.1970.
[176] L.C. Wilkins and P. A.Wintz,“Image coding by coding contours,” in Proc. ICOC, vol.1, pp.2.22-2.23,1970.
[177] W. F. Schreiber, T. S. Huang and O. J. Tretiak,“Contour coding of images,” in Picturebandwidth compression, Gordon&Breach, pp.443-448,1972.
[178] J. Murayama, T. Miyauchi and N. Shirota,“Image sequence coding using a contour-basedmethod,” in IEEE International Conference on Image Processing, vol.1, pp.546-549,1995.
[179] L. Labelle, D. Lauzon, J. Konrad and E. Dubois,“Arithmetic Coding of A losslesscontour-based representation of label images,” in IEEE International Conference on ImageProcessing, vol.1, pp.261-265,1998.
[180] N. Adami, P. Gallina, R. Leonardi and A. Signoroni,“Progressive contour coding in thewavelet domain,” in Lecture Notes in Computer Science, vol.3893, pp.179-188,2006.
[181] A. Akimov, A. Kolesnikov and P. Fr nti,“Lossless compression of map contours by contexttree modeling of chain codes,” in Pattern Recognition, vol.40(3), pp.944-952, Mar.2007.
[182] S. L. Horowitz and T. Pavlidis,“Picture segmentation by a tree traversal algorithm,” in Journalof the ACM, vol.23(2), pp.368-388, Apr.1976.
[183] J. M. Beaulieu and M. Goldberg,“Step-wise optimization for hierarchical picturesegmentation,” in IEEE Conference on Computer Vision and Pattern Recognition, pp.59-64,1983.
[184] M. Kocher and R. Leonardi,“Adaptive region growing technique using polynomial functionsfor image approximation,” in Signal Processing, vol.11(1), pp.47-60, Jul.1986.
[185] R. M. Haralick and L. G. Shapiro,“'Image segmentation techniques,” in Computer Vision,Graphics, and Image Processing, vol.29(1), pp.100-132, Jan.1985.
[186] M. Hotter,“Object-oriented analysis-synthesis coding based on moving two dimensionalobjects,” in Signal Processing: Image Communication, vol.2(4), pp.409-428, Dec.1990.
[187] M. Hotter,“Optimization and efficiency of an object oriented analysis-synthesis coder,” inIEEE Transactions on Circuits and Systems for Video Technology, vol.4(2), pp.181-194, Apr.1994.
[188] P. Gerken,“Object-based analysis-synthesis coding of image sequences at very low bit rates,”in IEEE Transactions on Circuits and Systems for Video Technology, vol.4(3), pp.228-235,Jun.1994.
[189] J. Ostermann,“Object-based analysis-synthesis coding (OBASC) based on the source modelof moving flexible3D-objects,” in IEEE Transactions on Image Processing, vol.3(5), pp.705-11, Sep.1994.
[190] K. Aizawa, H. Harashima and T. Saito,“Model-based analysis synthesis image coding(MBASIC) system for a person's face,” in Signal Processing: Image Communication, vol.1(2),pp.139-152, Oct.1989.
[191] H. Li, P. Roivainern and R. Forchheimer.“3-D motion estimation in model-based facial imagecoding,” in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.15(6), pp.545-555, Jun.1993.
[192] C. Choi, K. Aizawa, H. Harashima and T. Takebe,“Analysis and synthesis of facial imagesequences in model based image coding,” in IEEE Transaction on Circuits and Systems forVideo Technology, vol.4(3), pp.257-275, Jun.1994.
[193] N. S. Jayant, J. D. Johnston and R. J. Safranek,“Signal compression based on models ofhuman perception,” in Proceeding of the IEEE, vol.81(10), pp.1385-1422, Oct.1993.
[194] R. J. Safranek and J. D. Johnston,“A perceptually tuned subband image coder with imagedependent quantization and post-quantization data compression,” in IEEE InternationalConference on Acoustics, Speech, and Signal Processing. vol.3, pp.1945-1948,1989.
[195] C. Chou and Y. Li,“A perceptually tuned subband image coder based on the measure ofjust-noticeable-distortion profile,” in IEEE Transactions on Circuits and Systems for VideoTechnology, vol.5(6), pp.467-476, Dec.1995.
[196] A. Watson,“DCT quantization matrices visually optimized for individual images,” inProceedings of SPIE International Conference on Human Vision, Visual Processing, and DigitalDisplay-IV, vol.1913, pp.202-216,1993.
[197] S. Daly,“The Visible Differences Predictor: An algorithm for the Assessment of ImageFidelity”, in In: Digital Images and Human Vision, A.B. Watson, editor, MIT Press, Cambridge,Massachusetts,1993.
[198] X. Yang, W. Lin, Z. Lu, E. Ong and S. Yao,“Just-noticeable-distortion profile with nonlinearadditivity model for perceptual masking in color images,” in IEEE International Conference onAcoustics, Speech, Signal Processing, vol.3, pp.609-612,2003.
[199] X. Yang, W. Lin, Z. Lu, E. Ong and S. Yao,“Motion-compensated residue pre-processing invideo coding based on just-noticeable-distortion profile,” in IEEE Transactions on Circuits andSystems for Video Technology, vol.15(6), pp.742-750, Jun.2005.
[200] X. Yang, W. Lin, Z. Lu, E. Ong and S. Yao,“Just noticeable distortion model and itsapplications in video coding,” in Signal Processing: Image Communication, vol.20(7), pp.662-680, Aug.2005.
[201] L. Ma, N. King, F. Zhang and S. Li,“Adaptive block-size transform based just-noticeabledifference model for images/videos,” in Signal Processing: Image Communication, vol.26(3),pp.162-174, Mar.2011.
[202] P. Ndjiki-Nya, B. Makai, G. Bl ttermann, A. Smolic, H. Schwarz and T. Wiegand,“ImprovedH.264/AVC Coding using texture analysis and synthesis,” in IEEE International Conference onImage Processing, vol. III, pp.849-852,2003.
[203] A. Stojanovic, M. Wien and J. Ohm,“Dynamic texture synthesis for H.264/AVC inter coding,”in IEEE International Conference on Image Processing, pp.1608-1611,2008.
[204] A. Stojanovic and P. Kosse,“Extended dynamic texture prediction for H.264/AVC intercoding,” in IEEE International Conference on Image Processing, pp.2045-2048,2010.
[205] C. Zhu, X. Sun, F. Wu and H. Li,“Video coding with spatio-temporal texture synthesis,” inIEEE International Conference on Multimedia and Expo, pp.112-115,2007.
[206] C. Zhu, X. Sun; F. Wu and H. Li,“Video coding with spatio-temporal texture synthesis,” inIEEE International Conference on Multimedia and Expo, pp.112-115,2007.
[207] O. Bryt and M. Elad,“Compression of facial images using the K-SVD algorithm,” in Journalof Visual Communication and Image Representation, vol.19(4), pp.270-283, May2008.
[208] Z. Shi, X. Sun and F. Wu,“Adaptive DCT-Domain Down-Sampling and Learning BasedMapping for Low Bit-Rate Image Compression,” in Lecture Notes in Computer Science, vol.5879, pp.222-231,2009.
[209] B. Bai, L. Cheng, C. Lei, Pierre Boulanger and Janelle Harms,“Learning-based MultiviewVideo Coding,” in Picture Coding Symposium, pp.201-204,2009.
[210] H. Harashima and F. Kishino,“Intelligent Image Coding and communications with RealisticSensations–Recent Trends,” in IEICE Transactions, vol. E74-B(6), pp.1582-1592, Jun.1991.
[211] R. M. Haralick,“Statistical and structural approaches to texture,” in Proceeding of the IEEE,vol.67(5), pp.786-804, May1979.
[212] R. M. Haralick and L. G. Shapiro,“Computer and Robot Vision,” in Addison-Wesley,1992.
[213] C. Lan, J. Xu, F. Wu and G. J. Sullivan,“Screen content coding,” in document JCTVC-B084,Geneva, Switzerland, Jul2010.
[214] C. Lan, J. Xu, F. Wu and G. Sullivan,“Screen content coding results using TMuC,” indocument JCTVC-C276, Guangzhou, China, Oct.2010.
[215] H. Cheng, Y. Shen, J. Wu and K. Aizawa,“High efficient distributed video coding withparallelized design for cloud computing,” in ACM international conference on Multimedia, pp.1257-1260,2011.
[216] R. Pereira and K. Breitman,“A Cloud Based Architecture for Improving Video CompressionTime Efficiency: the Split&Merge Approach,” in Proceedings of Data Compression Conference,pp.471,2011.
[217] F. W. Campbell and J. G. Robson,“Application of Fourier analysis to the visibility of gratings,”in Journal of Physiology, vol.197(3), pp.551-566, Aug.1968.
[218] D. H. Hubel and T. N. Wiesel,“Receptive fields of single neurons in the cat's striate cortex,” inJournal of Physiology, vol.148, pp.574-591, Oct.1959.
[219] B. A. Olshausen, P. Sallee and M. S. Lewicki,“Learning sparse image codes using a waveletpyramid architecture,” in Advances in Neural Information Processing Systems, vol.13, pp.887-893,2000.
[220] A. Hyvarinen and P. O. Hoyer,“A two-layer sparse coding model learns simple and complexcell receptive fields and topography from natural images,” in Vision Research, vol.41(18), pp.2413-2423, Aug.2001.
[221] E. J. Candes, J. Romberg and T. Tao,“Robust uncertainty principles: exact signalreconstruction from highly incomplete frequency information,” in IEEE Transactions onInformation Theory, vol.52(2), pp.489-509, Feb.2006.
[222] D. L. Donoho,“Compressed sensing,” in IEEE Transactions on Information Theory, vol.52(4),pp.1289-1306, Apr.2006.
[223] J. L. Mannos and D. L. Sakrison,“The effects of a visual fidelity criterion on the encoding ofimages,” in IEEE Transactions on Information Theory, vol.20(4), pp.525-536, Jul.1974.
[224] J. O. Limb,“Distortion criteria of the human viewer,” in IEEE Transactions on Systems, Man,and Cybernetics, vol.9(12), pp.778-793, Dec.1979.
[225] Z. Wang, A. C. Bovik, H. R. Sheikh and E. P. Simoncelli.“Image quality assessment: Fromerror visibility to structural similarity,” in IEEE Transaction on Image Processing, vol.13(4), pp.600-612, Apr.2004.
[226] H. R. Sheikh and A. C. Bovik,“Image information and visual quality,” in IEEE Transactionson Image Processing, vol.15(2), pp.430-444, Feb.2006.
[227] D. M. Chandler and S. S. Hemami,“VSNR: A Wavelet-Based Visual Signal-to-Noise Ratio forNatural Images,” in IEEE Transactions on Image Processing, vol.16(9), pp.2284-2298, Sept.2007.
[228] S. Wang, A. Rehman, Z. Wang, S. Ma and W. Gao,“SSIM-Motivated Rate-DistortionOptimization for Video Coding,” in IEEE Transactions on Circuits and Systems for VideoTechnology, vol.22(4), pp.516-529, Apr.2012.
[229] T. Ou, Y. Huang and H. H. Chen,“SSIM-Based Perceptual Rate Control for Video Coding,” inIEEE Transactions on Circuits and Systems for Video Technology, vol.21(5), pp.682-691,2011.
[230] W. Lin and C. C. Jay Kuo,“Perceptual Visual Quality Metrics: A Survey”, in Journal of VisualCommunication and Image Representation, vol.22(4), pp.297-312, May2011.
[231] K. Seshadrinathan and A.C. Bovik “Automatic prediction of perceptual quality of multimediasignals—a survey,” in International Journal of Multimedia Tools and Applications, SpecialIssue on Survey Papers in Multimedia by World Experts, vol.51(1), pp.163-186, Jan.2011.
[232] A. K. Moorthy and A. C. Bovik,“Visual Quality Assessment Algorithms: What Does theFuture Hold?,” in International Journal of Multimedia Tools and Applications, Special Issue onSurvey Papers in Multimedia by World Experts, vol.51(2), pp.675-696, Feb.2011.
[233] M. Kampmann and J. Ostermann.“Automatic adaptation of a face model in a layered coderwith an object-based analysis-synthesis layer and a knowledge-based layer,” in SignalProcessing: Image Communications, vol.9(3), pp.201-220, Mar.1997.
[234] P. Eisert and B. Girod,“Model-based coding of facial image sequences at varying illuminationconditions,” in Proceedings of Image and Multidimensional Digital Signal ProcessingWorkshop, pp.119-122, July1998.
[235] A. M. Tekalp and J. Ostermann.“Face and2D mesh animation in MPEG-4,” in SignalProcessing: Image Communications. Special Issue on MPEG-4, vo.15(4), pp.387-421, Jan.2000.
[2] MPEG.“Coding of moving pictures and associated audio—for digital storage media at up toabout1.5Mbit/s—Part2: Video,” ISO/IEC11172-2(MPEG-1),1993.
[3] ITU-T.“Video codec for audio sisual services at px64kbit/s,” in ITU-T Recommendation H.261,1993.
[4] ITU-T.“Information technology—generic coding of moving pictures and associated audioinformation: video,” in ITU-T Recommendation H.262|ISO/IEC13818-2(MPEG-2),1995.
[5] ITU-T.“Video coding for low bitrate communication,” ITU-T Recommendation H.263,1998.
[6] ITU-T.“Advanced video coding for generic audio visual services,” in ITU-T Rec.H.264andISO/IEC14496-10(MPEG-4AVC), ITU-T and ISO/IEC JTC1, version1, May2003.
[7] AVS Workgroup.“Information technology—advanced coding of audio and video—Part2: video,”in AVS1-P2,2005.
[8] B. Bross, W. J. Han, G. J. Sullivan, J. R. Ohm and T. Wiegand,“Text of ISO/IEC DIS23008-2High Efficiency Video Coding,” in document JCTVC-N12935, Stockholm, Sweden, July2012.
[9] S. Ma and C. C. Kuo,“High-definition video coding with super-macroblocks,” in Proc. SPIEVisual Commun. Image Process., vol.6508,2007.
[10] Il-Koo Kim, Ken McCann, Kazuo Sugimoto and et al.,“HM9: High Efficiency Video Coding(HEVC) Test Model9Encoder Description,” JCTVC-N12935, Shanghai, Oct.2012.
[11] J.-H. Min, S. Lee, I. K. Kim, W. J. Han, J. Lainema and K. Ugur,“Unification of the DirectionalIntra Prediction Methods in TMuC,” JCTVC-B100, Geneva, Switzerland, Jul2010.
[12] TK Tan and Frank Bossen,“TE5: Results for Simplification of Unified Intra Prediction,”JCTVC-C042, Guangzhou, China, Oct2010.
[13] J. Chen, V. Seregin, S. Lee, W. Han, J. Kim, B.M. Jeon,“CE6.a.4: Chroma intra prediction byreconstructed luma samples,” JCTVC-E266, Geneva, CH, March2011.
[14] Sandeep Kanumuri and Frank Bossen,“CE6.e/f: Planar mode experiments and results,” indocument JCTVC-E321, Geneva, CH, March2011.
[15] K. R. Rao and P. Yip,“Discrete Cosine Transform: Algorithms, Advantages, Applications,” SanDiego, CA: Academic,1990.
[16] W. K. Pratt, J. Kane and H. C. Andrews,“Hadamard transform image coding,” in Proceeding ofthe IEEE, vol.57, Jan.1969, pp.58-68.
[17] K. Karhunen and Kari,“über Lineare Methoden in der Wahrscheinlichkeitsrechnung,” in Ann.Acad. Sci. Fennicae. Ser. A. I. Math.-Phys., no.37,1947, pp.1-79.
[18] R. M. Gray and D. L. Neuhoff,“Quantization,” IEEE Transactions on Information Theory,” vol.44, May1977, pp.2325-2383.
[19] J. Rissanen and G. G. Langdon,“Arithmetic coding,” IBM Journal of Research andDevelopment, vol.23,1979, pp.149-162.
[20] H C Andrews and W K Pratt,“Fourier Transform Coding of Images,” Hawaii Intl. Conf. onSystem Sciences, Sep1967.
[21] B. Bross H., Kirchhoffer, H. Schwarz and T. Wiegand,“Fast intra encoding for fixed maximumdepth of transform quadtree” JCTVC-C311, Guangzhou, China, Oct2010.
[22] T. Wiegand, H. Schwarz, B. Bross H., Kirchhoffer, X. Wang and A. Fuldseth,“BoG report:residual quadtree structure” JCTVC-C319, Guangzhou, China, Oct2010.
[23] I.-K Kim, W.-J Han, J. H. Park and X. Zheng,“CE2: Test results of asymmetric motionpartition (AMP),” in document JCTVC-F379, July2011.
[24] S. F. Chang, W. L. Chen and D.G. Messerschmitt,“Video Compositing in the DCT Domain,” inIEEE Workshop on Visual Signal Processing and Communications, pp.138-143,1992.
[25] Andrei Sharf, Marc Alexa and Daniel Cohen-Or.“Context-based surface completion,” ACMTransactions on Graphics, vol.23(3),878-887,2004.
[26] Y. Ye and M. Karczewicz,“Improved H.264Intra coding based on bi-directional Intraprediction, directional transform and adaptive coefficient scanning,” in IEEE InternationalConference on Image Processing (ICIP), pp.2116-2119, Oct.2008.
[27] Y. Su and M. Sun,"Fast Multiple Reference Frame Motion Estimation for H.264/AVC," inIEEE Trans. Circuits Syst. Video Technol., vol.16(3), pp.447-452, Mar.2006.
[28] R. Sj berg, D. Flynn, Y. Chen, Y. K. Wang, TK Tan and W. K. Wan,“JCT-VC AHG report:Reference picture buffering and list construction (AHG21),” JCT-VC Document, JCTVC-G021,Geneva, Switzerland, November2011.
[29] Y. Chen, C. Muhammed, W. Chien and et al.,“Comments on Generalized P and B Pictures,”JCTVC-D401, Daegu, KR, Jan.2011.
[30] Y Ye and Y. He,“AHG21: Reference picture lists combination syntax,” JCTVC-H0137, SanJosé, CA, USA, February2012.
[31]A.Fujibayashi and F.Bossen,“CE93.2d Simplified Motion vector prediction,” JCTVC-D231,Daegu Korea, Jan.2011
[32] E. Alshina, J. Chen, E. Alshin, N. Shlyakhov and W.-J. Han,“Experimental results of DCT-IFby samsung," JCTVC-D344, Daegu Korea, Jan.2011.
[33] J. Chen, E. Alshina and W.-J. Han,"Experimental results of DCTIF application for Chroma MCby Samsung", JCTVC-D347, Daegu Korea, Jan.2011.
[34] T. Chujoh and R. Noda,“Internal bit depth increase except frame memory,” ITU-T SG16Q.6Document, VCEG-AF07,32nd VCEG Meeting, San Jose, USA, April2007.
[35] K. Ugur, J. Lainema and A. Hallapuro,“High precision bi-directional averaging,” JCTVC-D321,Daegu Korea, Jan.2011.
[36] Y. Huang, B. Bross, M. Zhou and et al.“CE9：Summary report of core experiment on MVcoding and skip/merge operations,” JCTVC-F029, Torino, IT, Jul.2011.
[37] A. Saxena and F. Fernandes,“CE7: Mode-dependent DCT/DST for intra prediction in videocoding,” JCTVC-D033, Daegu, Korea, Jan.2011.
[38] Ankur Saxena and Felix C. Fernandes,“CE7: Mode-dependent DCT/DST without4×4fullmatrix multiplication for intra prediction”, JCTVC-E125, Geneva, CH, March2011.
[39] C. Fu, C. Chen, Y. Huang and et al.“CE10subtest3: Quadtree-based adaptive offset,”JCTVC-C147,2010.
[40] Y. Zheng, M. Coban and M. Karczewicz “CE13: Mode Dependent Hybrid Intra Smoothing,”JCTVC-D282, Daegu, Jan.2011.
[41] Y. Zheng, M. Coban, X. Wang, J. Sole, R. Joshi and M. Karczewicz,“CE11: Mode DependentCoefficient Scanning”, Doc. JCTVC-D393, Daegu, KR, Jan.2011.
[42] G. Bj ntegaard and K. Lillevold,“Context-adaptive VLC (CVLC) coding of coefficients,”JVT-C028,3rd Meeting: Fairfax, Virginia, USA,6-10May2002.
[43] Q. Wang, D. Zhao and W. Gao,“Context-Based2D-VLC Entropy Coder in AVS Video CodingStandard,” in Journal of Computer Science&Technology. vol.21(3), pp.315-322, May2006
[44] D. Marpe, H. Schwarz and T. Wiegand,“Context-Based Adaptive Binary Arithmetic Coding inthe H.264/AVC Video Compression Standard,” IEEE Trans. on Circuits and Systems for VideoTechnology, vol.13, issue.7, pp.620-636,2003.
[45] M. Budagavi, V. Sze, M. Demircin and et al.“Video coding technology proposal by TexasInstruments,” JCTVC-A101, Desden, April2010.
[46] R. Forchheimer and O. Fahlander,“Low bit-rate coding through animation,” in Proc. Int.Picture Coding Symp.(PCS), Davis, CA, pp.113-114,1983.
[47] R. Forchheimer, O. Fahlander and T. Kronander,“A semantic approach to the transmission offace images,” in Proc. Int. Picture Coding Symp., Cesson-Sevigne, France,1984.
[48] W. J. Welsh,“Model-based coding of moving images at very low bit rates,” in Proc. Int. PictureCoding Symp., Stockholm, Sweden,1987.
[49] K. Aizawa,“Model-based analysis-synthesis image coding system for very low-rate imagetransmission,” in Proc. Int. Picture Coding Symp., Turin, Italy,1988.
[50] K. Aizawa, H. Harashima and T. Saito,“Model-based analysis-synthesis image coding(MBASIC) for a person’s face,” in Image Commun., vol.1(2), pp139-152,1989.
[51] H. G. Musmann, M. Hotter and J. Ostermann,“Object-oriented analysis-synthesis of movingimages,” in Image Commun., vol.1(2), pp.117-138,1989.
[52] J. Y. Wang and E. H. Adelson “Representing moving images with layers,” in IEEE Trans. ImageProcess., vol.3(5), pp.625-638,1994.
[53] D. Chai and K. Ngan,“Foreground/background video coding scheme,” in Proc. IEEE Int. Symp.Circuits Syst., Hong Kong, vol.2, pp.1448-1451, June,1997.
[54] I. Martins and L. Corte-Real,“A video coder using3-D model based background for videosurveillance applications,” in Proc. IEEE Int. Conf. Image Process., pp.919-923,1998.
[55] I. E. G. Richardson,“H.264and MPEG-4video compression: video coding for next generationmultimedia,” in John Wiley&Sons Ltd, Chichester, England, pp.136-138,2003.
[56] K. Toyama, J. Krumm, B. Brumitt and B. Meyers,“Wallflower: principles and practice ofbackground maintenance,” in Proc. Int. Conf. Computer Vision, pp.255-261,1999.
[57] I. Haritaoglu, D. Harwood and L. Davis,“W4: real-time surveillance of people and theiractivities,” in IEEE Trans. Pattern Anal. Mach. Intell., vol.22(8),809-830,2000.
[58] A. Elgammal,“Efficient nonparametric kernel density estimation for real time computer vision,”in Ph.D. Thesis, Rutgers, the State University of New Jersey,2002.
[59] A. Elgammal, D. Harwood and L. Davis,“Non-parametric model for background subtraction,”in Proc. Sixth European Conf. Computer Vision, vol.2, pp.751-767,2000.
[60] Y. Heikh and M. Shah,“Bayesian modeling of dynamic scenes for object detection,” in IEEETrans. Pattern Anal. Mach. Intell., vol.27(11), pp.1778-1792,2005.
[61]L. Cheng, M. Gong, D. Schuurmans and T. Caelli,“Real-time discriminative backgroundsubtraction,” in IEEE Trans. Image Process., vol.20(5), pp.1401-1414,2011.
[62] J. K. Suhr, H. G. Jung, G. Li and et al.“Mixture of Gaussians-based Background Subtractionfor Bayer-Pattern Image Sequences,” in IEEE Trans. Circuits Syst. Video Technol., vol.21(3),pp.365-370,2010.
[63] J. Ding, M. Li, K. Huang and T. Tan,“Modeling complex scenes for accurate moving objectssegmentation,” in Proc. Tenth Asian Conf. Computer Vision, pp.592-604,2010.
[64] E. Francois, J.-F. Vial and B. Chupeau,“Coding algorithm with region-based motioncompensation,” in IEEE Trans. Circuits Syst. Video Technol. vol.7(1), pp.97-108,1997.
[65] A. Vetro, T. Haga, K. Sumi and et al.,“Object-based coding for long-term archive ofsurveillance video,” in Proc. IEEE Int. Conf. Multimedia and Expo, pp.417-420,2003.
[66] R.V. Babu and A. Makur,“Object-based surveillance video compression using foregroundmotion compensation,” in Int. Conf. Control, Automatic, Robotics and Vision,2006.
[67] A. Hakeem, K. Shafique and M. Shah,“An object-based video coding framework for videosequences obtained from static cameras,” in Proc. ACM Int. Conf. on Multimedia, pp.608-617,2005.
[68] D. Venkatraman and A. Makur,“A compressive sensing approach to object-based surveillancevideo coding,” in IEEE Int. conf. Acoustics, Speech, Signal Process., pp.3513-3516, Apr.2009.
[69] X. Jin and S. Goto,“Encoder adaptable difference detection for low power video compressionin surveillance system,” in Sig. Proc.: Image Comm., vol.26(3), pp.130-142,2011.
[70] T. C. Chen, Y. W. Huang, C. Y. Tsai, C. T. Huang and L. G. Chen,"Single reference framemultiple current macroblocks scheme for multi-frame motion estimation in H.264/AVC", inProc. IEEE Int. Symp. Circuits Syst., vol.2, pp.1790-1793,2005.
[71] R. Ding, Q. Dai, W. Xu, D. Zhu and H. Yin,"Background-frame based motion compensationfor video com-pression," in Proc. IEEE Int. Conf. Multimedia and Expo,2004
[72] M. Paul, W. Lin, C. T. Lau and B. S. Lee,"Video coding using the most common frame inscene," in Interna-tional conference on Acoustics, Speech and Signal processing, pp.734-737,2010
[73] X. Zhang, L. Liang, Q. Huang and W. Gao,"An efficient coding scheme for surveillance videoscaptured by stationary cameras," in Proc. Visual Commun. Image Process., July2010
[74] M. Paul, W. Lin, C. T. Lau and B. S. Lee,"Explore and model better I-frame for video coding,"in IEEE Transactions on Circuits and Systems for Video Technology, vol.21(9), pp.1242-1254,2011.
[75] B. P. L. Lo and S. A. Velastin,“Automatic congestion detection system for undergroundplatforms,” in Proc. ISIMP2001, pp.158-161, May2001.
[76] R. Cucchiara, C. Grana, M. Piccardi and A. Prati,“Detecting moving objects, ghosts, andshadows in video streams,” in IEEE Trans. on Patten Anal. and Machine Inteli., vol.25(10), pp.1337-1442,2003
[77] M. Piccardi,“Background subtraction techniques: a review,” in Proc. IEEE Man andCybernetics,2004.
[78] A. Elgammal, D. Hanvood and L.S. Davis,“Nonparametric model for background subtraction,”in Proc. ECCV2000, pp.751-767, Jun.2000
[79] N.M. Oliver, B. Rosario and A.P. Pentland,“A Bayesian computer vision system for modelinghuman interactions,” in IEEE Trans. on Paftern Anal. and Machine Intell., vol.22(8), pp.831-843,2000.
[80] K. Fukunaga,“The Estimation of the Gradient of a Density Function with Applications inPattern Recognition,” in IEEE Transactions on Information Theory, vol.4(2), pp.32-40,1975
[81] C. Wren, A. Azarhayejani, T. Darrell and A.P. Pentland,“Pfinder: real-time tracking of thehuman body,” in IEEE Trans. on Pattern Anal. and Machine Intell., vol.19(7), pp.780-785,1997
[82] M. Haque, M. Murshed and M. Paul,“Improved Gaussian mix-tures for robust object detectionby adaptive multi-background generation,” in IEEE Conf. on Computer Vision and PatternRecognition,2008.
[83] K. Kim, T. H. Chalidabhongse, D. Harwood and et al.“Real-time foreground-backgroundsegmentation using codebook model,” in Real-time imaging, vol.20(11), pp.172-185,2005.
[84] B. Girod,“The Efficiency of Motion-compensating Prediction for Hybrid Coding of VideoSequences,” in IEEE J. Selecl. Areas Commun., vol.5(8), pp.1140-1154,1987.
[85] B. Girod,“Efficiency Analysis of Multihypothesis Motion-compensated Prediction for VideoCoding,” in IEEE Transaction on Image Process., vol.9(2), pp.173-183,2000.
[86] N. S. Jayant and P. Noll,“Digital Coding of Waveforms. Englewood Cliffs,” in NJ:Prentice-Hall,1984.
[87] F. Pan, X. Lin, R. Susanto, K. P. Lim, Z. G. Li, G. N. Feng, D. J. Wu and S. Wu,“Fast modedecision algorithm for intraprediction in H.264/AVC Video Coding,” in IEEE Trans. CircuitsSyst. Video Technol., vol.15, pp.813-822, Jul.2005.
[88] D. Wu, F. Pan, K. P. Lim, S. Wu, Z. G. Li, X. Lin, R. Susanto and C. C. Kuo,“Fast inter modedecision in H.264/AVC Video Coding,” in IEEE Trans. Circuits Syst. Video Technol., vol.15,pp.953-958, Jul.2005.
[89] G. J. Sullivan and T. Wiegand,“Rate-distortion optimization for video compression,” in IEEESignal Processing Magazine, vol.15, pp.74-90, Nov.1998.
[90] Y. K. Tu, J. F. Yang and M. T. Sun,“Efficient rate-distortion estimation for H264/AVC coders,”in IEEE Trans. Circuits Syst. Video Technol., vol.16, pp.600-611, May2006.
[91] M. G. Sarwer and L. M. Po,“Fast bit rate estimation for mode decision of H.264/AVC,” inIEEE Trans. Circuits Syst. Video Technol., vol.17, pp.1402-1407, Oct.2007.
[92] Y. K. Tu, J. F. Yang and M. T. Sun,“Rate-Distortion Modeling for Efficient H.264/AVCEncoding,” in IEEE Trans. Circuits Syst. Video Technol., vol.17, pp.530-543, May2007,
[93] C. C. Chen, C. O. T. C and H. H. Wu,“Region of Interest Determined by Picture Contents inJPEG2000,” in IEEE International Symposium on Circuits and Systems, vol.2, pp.868-871,2003.
[94] D. Nistr, C. Christopoulos,“Lossless Region of Interest Coding,” in Signal Processing, vol.78,pp.1-17,1999.
[95] D. N., D. A. and K. D.,“Low Bit-rate Coding of Image Sequences Using Adaptive Regions ofInterest,” in IEEE Transaction On Circuits and Systems for Video Technology, vol.8(8), pp.928-934,1998.
[96] M. M. and M. K., F. K.“A Hierarehical Video Compression Method Using Object Coding,” inProceedings of world Automation Congress, vol12, pp.345-350,2002.
[97] M. M., Hannuksela, Y. kui Wang and et al.“Sub-picture: Roi Coding and UnequalErrorProtection,” in IEEE International Conference on Image Processing. Rochester, New York,USA,537-540,2002.
[98] Y. Liu, Z. G. Li and Y. C. Soh,“Region-of-interest Based Resource Allocation forConversational Video Communication of H.264/AVC,” in IEEE Transaction On Circuits andSystems for Video Technology, vol18(1), pp.134-139,2008.
[99] Y. Liu, Z. G. Li and Y. C. Soh,“A Novel Rate Control Scheme for Low Delay VideoCommunication of H.264/AVC Standard,” in IEEE Transaction On Circuits and Systems forVideo Technology, vol.17(1),2007.
[100] R. K., O. A. and V. M.,“Bit Allocation for Dependent Quantization with Applications toMultiresolution and Mpeg Video Coders,” in IEEE Trans. Signal Processing, vol.3(5), pp.533-545,1994.
[101] J. R. Ding and J. F. Yang,“Adaptive group-of-pictures and scene change detection methodsbased on existing H.264advanced video coding information,” in IET Image Processing, vol2(2), pp.85-94,2008.
[102] T. Wiegand, X. Zhang and B. Girod,“Long-term memory motion-compensated prediction,” inIEEE Trans. Circuits Syst. Video Technol., vol.9(1), pp.70-84,1999.
[103]M. Tiwari, P.C. Cosman,“Selection of long-term reference frames in dual-frame video codingusing simulated annealing,” in IEEE Signal Processing Letters, vol.15, pp.249-252,2008.
[104] D. Liu, D. Zhao, X. Ji and et al.,“Dual frame motion compensation with optimal long-termreference frame selection and bit allocation,” in IEEE Trans. Circuits Syst. Video Technol., vol.20(3), pp.325-339, Mar.2010.
[105] A. Leontaris and P. C. Cosman,“Compression efficiency and delay tradeoffs for hierarchicalB-picture frames and pulsed-quality frames,” in IEEE Trans. Image Process., vol.16(7), pp.1726-1740, Jul.2007.
[106] H. Schwarz, D. Marpe and T. Wiegand,“Overview of the Scalable Video Coding Extension ofthe H.264/AVC Standard,” in IEEE Trans. Circuits Syst. Video Technol., vol.17(9), pp.1103-1120, Sep.2007.
[107] J. Xu, F. Wu and H. Li,“Encoding optimization to improve coding efficiency for low delaycases,” in JCT-VC document JCTVC-F701r1, Jul.2011.
[108] Frank Bossen,“HM8Common Test Conditions and Software Reference Configurations,” inJCT-VC document JCTVC-J1100, Jul.2012.
[109]G. Bjontegaard,“Calculation of average PSNR difference between RD-curves,” in documentVCEG-M33.doc, ITU-T VCEG,13th Meeting, Austin, TX, Apr.2001.
[110] A. Vetro, C. Christopoulos and H. Sun,“Video transcoding architectures and techniques: anoverview,” in IEEE Signal Processing Magazine, vol.20(2), pp.18-29, March2003.
[111] H. Sun, W. Kwok and J. W. Zdepski,“Architectures for mpeg compressed bitstream scaling,”in IEEE Transactions on Circuits and Systems for Video Technology, vol.6(2), pp.191-199,April1996.
[112] P. A. A. Assuncao and M. Ghanbari,“A frequency-domain video transcoder for dynamicbit-rate reduction of mpeg-2bit streams,” in IEEE Transactions on Circuits and Systems forVideo Technology, vol.8(8), pp.953-967, Dec1998.
[113] G. J. Shen, Y. He, W. Cao and S. Li,“MPEG-2to WMV transcoder with adaptive errorcompensation and dynamic switches,” in IEEE Transactions on Circuits and Systems for VideoTechnology, vol.16(12), pp.1460-1476, November2006.
[114] L. Yuan, F. Wu, Q. Chen, S. Li and W. Gao,“The fast close-loop video transcoder with limiteddrifting error,” in IEEE International Symposium on Circuits and Systems, pp.769-772, vol.3,Mar.2004.
[115]袁禄军，视频转码技术的研究及其应用，（博士论文）2005
[116] J. Xin, C. W. Lin and M. T. Sun,“Digital video transcoding,” in Proceeding of the IEEE, vol.93(1), pp.84-97, Jan.2005.
[117] T. Shanableh,“Hybrid dct/pixel domain architecture for heterogeneous video transcoding,” inSignal Processing: Image Communication, vol.18(8), pp.601-620, Sept.2003.
[118] H. Schwarz, D. Marpe and T. Wiegand,“Overview of the scalable video coding extension ofthe H.264standard,” in IEEE Transactions on Circuits and Systems for Video Technology, vol.17(9), pp.1103-1120, September2007.
[119] Y. Liang and Y.-P. Tan,“Methods and needs for transcoding mpeg-4fine granularity scalabilityvideo,” in IEEE International Symposium on Circuits and Systems, pp.719-722,2002.
[120] H. Sun, T. Chiang and X. Chen,“Digital video transcoding for transmission and storage,” inCRC Press, May2004.
[122] J. Youn, M.T. Sun and C.W. Lin,“Motion vector refinement for high performance transcoding,”in IEEE Trans. Multimedia, vol.1, pp.30-40, Mar.1999.
[123] Y. Shin, N. Son, N. D. Toan and G. Lee,“Low-complexity heterogeneous video transcoding bymotion vector clustering,” in Information Science and Applications,2010.
[124] K. T. Fung and W. C. Siu,“Low complexity H.263to H.264video transcoding using motionvector decomposition,” in IEEE Int. Symp. Circuits Syst.,2005.
[125] H. Kalva and P. Kunselmann,“Dynamic motion estimation for transcoding P frames in H.264to MPEG-2transcoders,” in IEEE T. Consum. Electr., vol.54, pp.657-661,2008.
[126] C. D. Wu and Y. Lin,“Efficient inter/intra mode decision for H.264/AVC inter frametranscoding” in Proc. IEEE Int. Conf. Image Process.,2009.
[127] P. Zhang, Q. M. Huang and W. Gao,“Key techniques of bit-rate reduction for H.264streams,”in Proc. Pacific-Rim Conf. Multimedia,2004.
[128] X. Lu, A. M. Tourapis, P. Yin and J. Boyce,“Fast mode decision and motion estimation forH.264with a focus on MPEG-2/H.264transcoding,” in IEEE Int. Symp. Circuits Syst.,2005.
[129] A. Vetro, H. Sun and Y. Wang,“Object-based transcoding for scalable quality of service,” inIEEE Int. Symp. Circuits and Systems,2000.
[130] T. Hata, N. Kuwahara, T. Nozawa and et al.“Surveillance system with object-aware videotranscoder,” in IEEE Int. Workshop on Multimedia Sig. Process.,2005
[131] D. Kubasov,“Mesh-based motion-compensated interpolation for side information extraction indistributed video coding,” in IEEE International Conference on Image Processing, pp.261-264,2006.
[132] A. Smolic, K. Mueller, N. Stefanoski, J. Ostermann, A. Gotchev, G. B. Akar, G. Triantafyllidisand A. Koz,“Coding algorithms for3DTV—a survey,” in IEEE Transactions on Circuits andSystems for Video Technology, vol.17(11), pp.1606-1621, Nov.2007.
[133] T. Sikora,“Trends and perspectives in image and video coding,” in Proceeding of the IEEE,vol.93(1), pp.6-17, Jan.2005.
[134] M. Kunt, A. Ikonomopoulos and M. Kocher,“Second-generation image-coding techniques,” inProceeding of the IEEE, vol.73(4), pp.549-574, Apr.1985.
[135] M. Civanlar, S. Rajala and W. Lee,“Second generation hybrid image-coding techniques,” inProceedings of SPIE Visual Communications and Image Processing, vol.707, pp.132-137,1986.
[136] X. Zhang, L. Liang, Q. Huang, Y. Liu, T. Huang and W. Gao,“An efficient coding scheme forsurveillance videos captured by stationary cameras,” in Proceedings of SPIE Conference onVisual Communications and Image Processing, vol.7744, pp.77442A-1-10,2010.
[137] H. Yue, X. Sun, F. Wu and J. Yang,“SIFT-based Image Compression,” in IEEE InternationalConference on Multimedia and Expo, pp.473-478,2012.
[138] P. Ndjiki-Nya, D. Doshkov, H. Kaprykowsky, F. Zhang, D. Bull and T. Wiegand,“Perception-oriented video coding based on image analysis and completion: A review,” inSignal Processing: Image Communication, vol.27(6), pp.579-594, Feb.2012.
[139] S. Wang, J. Fu, Y. Lu, S. Li and W. Gao,“Content-Aware Layered Compound VideoCompression,” in IEEE International Symposium on Circuits and Systems, pp.145-148,2012.
[140] H. Harashima, K. Aizawa and T. Saito,“Model based analysis synthesis coding ofvideotelephone images—conception and basic study of intelligent image coding,” inTransactions IEICE, vol. E72(5), pp.452-458, May1989.
[141] P. Cicconi, E. Reusens, F. Dufaux, I. Moccagatta, B. Rouchouze, T. Ebrahimi and M. Kunt,“New trends in image data compression,” in Computerized Medical Imaging and GraphicsJournal, vol.18(2), pp.107-124, Mar.1994.
[142] H. Li, A. Lundmark and R. Forchheimer,“Image sequence coding at very low bit rates: areview,” in IEEE Transactions on Image Processing, vol.3(5), pp.589-609, Sept.1994.
[143] D. E. Pearson,“Developments in model based video coding,” in Proceedings of the IEEE, vol.83(6), pp.892-906, June1995.
[144] K. Aizawa and T. Huang,“Model-based Image coding: advanced video coding Techniques forVery Low Bit-Rate Applications,” in Proceeding of the IEEE, vol.83(2), Feb.1995.
[145] B. Girod, K. Younes, R. Bernstein, P. Eisert, N. Farber, F. Hartung, U. Horn, E. Steinbach, K.Stuhlmuller and T. Wiegand,“Recent advances in video compression,” in IEEE InternationalSymposium on Circuits and Systems, vol.2, pp.580-583,1996.
[146] F. Pereira, Shih-fu Chang, R. Koenen, A. Puri and O. Avaro,“Introduction to the special issueon object-based video coding and description,” in IEEE Transaction on Circuits and Systemsfor Video Technology, vol.9(8), pp.1144-1146, Dec.1999.
[147] T. Sikora,“Trends and perspectives in image and video coding,” in Proceeding of the IEEE,vol.93(1), pp.6-17, Jan.2005.
[148] W. F. Schreiber, C. F. Knapp and N. D. Kay,“Synthetic highs—an experimental TV bandwidtheducation system,” in Journal of Society of Motion Picture and Television Engineers, vol.68,pp.525-537, Aug.1959.
[149] Musmann,“Source models for image sequence coding,” in Int. Workshop on Coding Techn.for Very Low Bit-rate video, University of Essex, UK, Apr.1994.
[150] V. Seferidis and M. Ghanbari,“General approach to block-matching motion estimation,” inOptical Engineering, vol.32(7), pp.1464-1474, Jul.1993.
[151] G. J. Sullivan and R. L. Baker,“Motion compensation for video compression using controlgrid interpolation,” in IEEE International Conference on Acoustics, Speech and SignalProcessing, pp.2713-2716,1996.
[152] H. Brusewitz,“Motion compensation with triangles,” in Proc.3rd International workshop on64k bits/s Coding of Moving Video, Sept.1990.
[153] O. D. Escoda, P. Yin, C. Dai and X. Li,“Geometric-adaptive bock partitioning for videocoding,” in IEEE International Conference on Acoustics, Speech and Signal Processing, vol.1,pp.657-660,2007.
[154] L. Guo, P. Yin and E. Francois,“TE:3simplified geometry block partitioning,” in documentJCTVC-B085, Geneva, Switzerland, Jul2010.
[155] D. Graham,“Image transmission by two-dimensional contour coding,” in Proceeding of theIEEE, vol.55(3), pp.336-346, Mar.1967.
[156] M. J. Biggar, O.J. Morris and A.G. Constantinides,“Segmented image coding: performancecomparison with the discrete cosine transform,” in IEE Proceedings, Part F, vol.135(2), pp.121-132, Apr.1988.
[157] M. Gilge, T. Engelhardt and R. Mehlan,“Coding of Arbitrarily Shaped Image Segments Basedon A Generalized Orthogonal Transform,” in Signal Processing: Image Communication, vol.1(2), pp.153-180, Oct.1989.
[158] P. Willemin, T. Reed and M. Kunt,“Image sequence coding by split and merge,” in IEEETransactions on Communications, vol.39(12), pp.1845-1855,1991.
[159] W. Li and M. Kunt,“Morphological segmentation applied to displaced frame differencecoding,” in Signal Processing, vol.38(1), pp.45-56, July1994.
[160] P. Salembier, L. Torres, F. Meyer and C. Gu,“Region-based video coding using mathematicalmorphology,” in Proceeding of the IEEE vol.83(6), pp.843-857, Jun.1995.
[161] F. Marqu′es, V. Vera and A. Gasull,“A hierarchical image sequence model for segmentation:application to object-based sequence coding,” in Proceedings of SPIE Visual Communicationsand Signal Processing, pp.554-563, Oct.1994.
[162] C. Gu and M. Kunt,“Very low bit-rate video coding using multi-criterion segmentation,” inIEEE International Conference on Image Processing, vol. II, pp.418-422, Nov.1994.
[163] H. G. Musmann, M. Hotter and J. Ostermann.“Object oriented analysis-synthesis coding ofmoving images,” in Singnal Procesing: Image communications, vol.1(2), pp.117-138, Oct.1989.
[164] P. Salembier, F. Marqu′es, M. Pard`as and et al.,“Segmentation-based video coding systemallowing the manipulation of objects,” in IEEE Transactions on Circuits and Systems for VideoTechnology, vol.7(1), Feb.1997.
[165] F. Parke,“Parameterized models for facial animation,” in IEEE Comput. Graph. Applicat.Mag., vol.12, pp.61-68, Nov.1982.
[166] R. Forchheimer, O. Fahlander and T. Kronander,“A semantic approach to the transmission offace images,” in International Picture Coding Symposium,1984.
[167] C. F. Hall,“Digital color image compression in a perceptual space,” in Doctoral Dissertation,University of Southern California Los Angeles, CA, USA,1978
[168] D. J. Sakrison,“Image coding applications of vision models,” in In: W. K. Pratt (Ed.), ImageProcessing Techniques, Academic Press, San Diego, CA pp.21-71,1979.
[169] Y. Li, X. Sun, H. Xiong and F. Wu,“Incorporating Primal Sketch Based Learning Into LowBit-Rate Image Compression,” in Proceedings of International Conference on Image Processing,vol.3, pp.173-176,2007.
[170] X. Sun and F. Wu,“Classified patch learning for spatially scalable video coding,” in IEEEInternational Conference on Image Processing, pp.2301-2304,2009.
[171] Y. Yang, O. C. Au, L. Fang, X. Wen and W. Tang.“Perceptual compressive sensing for imagesignals,” in IEEE International Conference on Multimedia and Expo, pp.89-92, June2009.
[172] M. R. Pickering, J. You, T. Ebrahimi and A. Perkis.“A compressive sensing approach toperceptual image coding,” in Proceedings of SPIE Applications of Digital Image ProcessingXXXIII, vol.7798, pp.77981E-1-11,2010.
[173] D. Kubasov,“Mesh-based motion-compensated interpolation for side information extraction indistributed video coding,” in IEEE International Conference on Image Processing, pp.261-264,2006.
[174] A. Smolic, K. Mueller, N. Stefanoski, J. Ostermann, A. Gotchev, G. B. Akar, G. Triantafyllidisand A. Koz,“Coding algorithms for3DTV—a survey,” in IEEE Transactions on Circuits andSystems for Video Technology, vol.17(11), pp.1606-1621, Nov.2007.
[175] L. C. Wilkins and P. A. Wintz,“Studies on data compression: part1: picture coding bycontours,” in Purdue University, School of Electronic Engineering, Tech. Report70-17, Sept.1970.
[176] L.C. Wilkins and P. A.Wintz,“Image coding by coding contours,” in Proc. ICOC, vol.1, pp.2.22-2.23,1970.
[177] W. F. Schreiber, T. S. Huang and O. J. Tretiak,“Contour coding of images,” in Picturebandwidth compression, Gordon&Breach, pp.443-448,1972.
[178] J. Murayama, T. Miyauchi and N. Shirota,“Image sequence coding using a contour-basedmethod,” in IEEE International Conference on Image Processing, vol.1, pp.546-549,1995.
[179] L. Labelle, D. Lauzon, J. Konrad and E. Dubois,“Arithmetic Coding of A losslesscontour-based representation of label images,” in IEEE International Conference on ImageProcessing, vol.1, pp.261-265,1998.
[180] N. Adami, P. Gallina, R. Leonardi and A. Signoroni,“Progressive contour coding in thewavelet domain,” in Lecture Notes in Computer Science, vol.3893, pp.179-188,2006.
[181] A. Akimov, A. Kolesnikov and P. Fr nti,“Lossless compression of map contours by contexttree modeling of chain codes,” in Pattern Recognition, vol.40(3), pp.944-952, Mar.2007.
[182] S. L. Horowitz and T. Pavlidis,“Picture segmentation by a tree traversal algorithm,” in Journalof the ACM, vol.23(2), pp.368-388, Apr.1976.
[183] J. M. Beaulieu and M. Goldberg,“Step-wise optimization for hierarchical picturesegmentation,” in IEEE Conference on Computer Vision and Pattern Recognition, pp.59-64,1983.
[184] M. Kocher and R. Leonardi,“Adaptive region growing technique using polynomial functionsfor image approximation,” in Signal Processing, vol.11(1), pp.47-60, Jul.1986.
[185] R. M. Haralick and L. G. Shapiro,“'Image segmentation techniques,” in Computer Vision,Graphics, and Image Processing, vol.29(1), pp.100-132, Jan.1985.
[186] M. Hotter,“Object-oriented analysis-synthesis coding based on moving two dimensionalobjects,” in Signal Processing: Image Communication, vol.2(4), pp.409-428, Dec.1990.
[187] M. Hotter,“Optimization and efficiency of an object oriented analysis-synthesis coder,” inIEEE Transactions on Circuits and Systems for Video Technology, vol.4(2), pp.181-194, Apr.1994.
[188] P. Gerken,“Object-based analysis-synthesis coding of image sequences at very low bit rates,”in IEEE Transactions on Circuits and Systems for Video Technology, vol.4(3), pp.228-235,Jun.1994.
[189] J. Ostermann,“Object-based analysis-synthesis coding (OBASC) based on the source modelof moving flexible3D-objects,” in IEEE Transactions on Image Processing, vol.3(5), pp.705-11, Sep.1994.
[190] K. Aizawa, H. Harashima and T. Saito,“Model-based analysis synthesis image coding(MBASIC) system for a person's face,” in Signal Processing: Image Communication, vol.1(2),pp.139-152, Oct.1989.
[191] H. Li, P. Roivainern and R. Forchheimer.“3-D motion estimation in model-based facial imagecoding,” in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.15(6), pp.545-555, Jun.1993.
[192] C. Choi, K. Aizawa, H. Harashima and T. Takebe,“Analysis and synthesis of facial imagesequences in model based image coding,” in IEEE Transaction on Circuits and Systems forVideo Technology, vol.4(3), pp.257-275, Jun.1994.
[193] N. S. Jayant, J. D. Johnston and R. J. Safranek,“Signal compression based on models ofhuman perception,” in Proceeding of the IEEE, vol.81(10), pp.1385-1422, Oct.1993.
[194] R. J. Safranek and J. D. Johnston,“A perceptually tuned subband image coder with imagedependent quantization and post-quantization data compression,” in IEEE InternationalConference on Acoustics, Speech, and Signal Processing. vol.3, pp.1945-1948,1989.
[195] C. Chou and Y. Li,“A perceptually tuned subband image coder based on the measure ofjust-noticeable-distortion profile,” in IEEE Transactions on Circuits and Systems for VideoTechnology, vol.5(6), pp.467-476, Dec.1995.
[196] A. Watson,“DCT quantization matrices visually optimized for individual images,” inProceedings of SPIE International Conference on Human Vision, Visual Processing, and DigitalDisplay-IV, vol.1913, pp.202-216,1993.
[197] S. Daly,“The Visible Differences Predictor: An algorithm for the Assessment of ImageFidelity”, in In: Digital Images and Human Vision, A.B. Watson, editor, MIT Press, Cambridge,Massachusetts,1993.
[198] X. Yang, W. Lin, Z. Lu, E. Ong and S. Yao,“Just-noticeable-distortion profile with nonlinearadditivity model for perceptual masking in color images,” in IEEE International Conference onAcoustics, Speech, Signal Processing, vol.3, pp.609-612,2003.
[199] X. Yang, W. Lin, Z. Lu, E. Ong and S. Yao,“Motion-compensated residue pre-processing invideo coding based on just-noticeable-distortion profile,” in IEEE Transactions on Circuits andSystems for Video Technology, vol.15(6), pp.742-750, Jun.2005.
[200] X. Yang, W. Lin, Z. Lu, E. Ong and S. Yao,“Just noticeable distortion model and itsapplications in video coding,” in Signal Processing: Image Communication, vol.20(7), pp.662-680, Aug.2005.
[201] L. Ma, N. King, F. Zhang and S. Li,“Adaptive block-size transform based just-noticeabledifference model for images/videos,” in Signal Processing: Image Communication, vol.26(3),pp.162-174, Mar.2011.
[202] P. Ndjiki-Nya, B. Makai, G. Bl ttermann, A. Smolic, H. Schwarz and T. Wiegand,“ImprovedH.264/AVC Coding using texture analysis and synthesis,” in IEEE International Conference onImage Processing, vol. III, pp.849-852,2003.
[203] A. Stojanovic, M. Wien and J. Ohm,“Dynamic texture synthesis for H.264/AVC inter coding,”in IEEE International Conference on Image Processing, pp.1608-1611,2008.
[204] A. Stojanovic and P. Kosse,“Extended dynamic texture prediction for H.264/AVC intercoding,” in IEEE International Conference on Image Processing, pp.2045-2048,2010.
[205] C. Zhu, X. Sun, F. Wu and H. Li,“Video coding with spatio-temporal texture synthesis,” inIEEE International Conference on Multimedia and Expo, pp.112-115,2007.
[206] C. Zhu, X. Sun; F. Wu and H. Li,“Video coding with spatio-temporal texture synthesis,” inIEEE International Conference on Multimedia and Expo, pp.112-115,2007.
[207] O. Bryt and M. Elad,“Compression of facial images using the K-SVD algorithm,” in Journalof Visual Communication and Image Representation, vol.19(4), pp.270-283, May2008.
[208] Z. Shi, X. Sun and F. Wu,“Adaptive DCT-Domain Down-Sampling and Learning BasedMapping for Low Bit-Rate Image Compression,” in Lecture Notes in Computer Science, vol.5879, pp.222-231,2009.
[209] B. Bai, L. Cheng, C. Lei, Pierre Boulanger and Janelle Harms,“Learning-based MultiviewVideo Coding,” in Picture Coding Symposium, pp.201-204,2009.
[210] H. Harashima and F. Kishino,“Intelligent Image Coding and communications with RealisticSensations–Recent Trends,” in IEICE Transactions, vol. E74-B(6), pp.1582-1592, Jun.1991.
[211] R. M. Haralick,“Statistical and structural approaches to texture,” in Proceeding of the IEEE,vol.67(5), pp.786-804, May1979.
[212] R. M. Haralick and L. G. Shapiro,“Computer and Robot Vision,” in Addison-Wesley,1992.
[213] C. Lan, J. Xu, F. Wu and G. J. Sullivan,“Screen content coding,” in document JCTVC-B084,Geneva, Switzerland, Jul2010.
[214] C. Lan, J. Xu, F. Wu and G. Sullivan,“Screen content coding results using TMuC,” indocument JCTVC-C276, Guangzhou, China, Oct.2010.
[215] H. Cheng, Y. Shen, J. Wu and K. Aizawa,“High efficient distributed video coding withparallelized design for cloud computing,” in ACM international conference on Multimedia, pp.1257-1260,2011.
[216] R. Pereira and K. Breitman,“A Cloud Based Architecture for Improving Video CompressionTime Efficiency: the Split&Merge Approach,” in Proceedings of Data Compression Conference,pp.471,2011.
[217] F. W. Campbell and J. G. Robson,“Application of Fourier analysis to the visibility of gratings,”in Journal of Physiology, vol.197(3), pp.551-566, Aug.1968.
[218] D. H. Hubel and T. N. Wiesel,“Receptive fields of single neurons in the cat's striate cortex,” inJournal of Physiology, vol.148, pp.574-591, Oct.1959.
[219] B. A. Olshausen, P. Sallee and M. S. Lewicki,“Learning sparse image codes using a waveletpyramid architecture,” in Advances in Neural Information Processing Systems, vol.13, pp.887-893,2000.
[220] A. Hyvarinen and P. O. Hoyer,“A two-layer sparse coding model learns simple and complexcell receptive fields and topography from natural images,” in Vision Research, vol.41(18), pp.2413-2423, Aug.2001.
[221] E. J. Candes, J. Romberg and T. Tao,“Robust uncertainty principles: exact signalreconstruction from highly incomplete frequency information,” in IEEE Transactions onInformation Theory, vol.52(2), pp.489-509, Feb.2006.
[222] D. L. Donoho,“Compressed sensing,” in IEEE Transactions on Information Theory, vol.52(4),pp.1289-1306, Apr.2006.
[223] J. L. Mannos and D. L. Sakrison,“The effects of a visual fidelity criterion on the encoding ofimages,” in IEEE Transactions on Information Theory, vol.20(4), pp.525-536, Jul.1974.
[224] J. O. Limb,“Distortion criteria of the human viewer,” in IEEE Transactions on Systems, Man,and Cybernetics, vol.9(12), pp.778-793, Dec.1979.
[225] Z. Wang, A. C. Bovik, H. R. Sheikh and E. P. Simoncelli.“Image quality assessment: Fromerror visibility to structural similarity,” in IEEE Transaction on Image Processing, vol.13(4), pp.600-612, Apr.2004.
[226] H. R. Sheikh and A. C. Bovik,“Image information and visual quality,” in IEEE Transactionson Image Processing, vol.15(2), pp.430-444, Feb.2006.
[227] D. M. Chandler and S. S. Hemami,“VSNR: A Wavelet-Based Visual Signal-to-Noise Ratio forNatural Images,” in IEEE Transactions on Image Processing, vol.16(9), pp.2284-2298, Sept.2007.
[228] S. Wang, A. Rehman, Z. Wang, S. Ma and W. Gao,“SSIM-Motivated Rate-DistortionOptimization for Video Coding,” in IEEE Transactions on Circuits and Systems for VideoTechnology, vol.22(4), pp.516-529, Apr.2012.
[229] T. Ou, Y. Huang and H. H. Chen,“SSIM-Based Perceptual Rate Control for Video Coding,” inIEEE Transactions on Circuits and Systems for Video Technology, vol.21(5), pp.682-691,2011.
[230] W. Lin and C. C. Jay Kuo,“Perceptual Visual Quality Metrics: A Survey”, in Journal of VisualCommunication and Image Representation, vol.22(4), pp.297-312, May2011.
[231] K. Seshadrinathan and A.C. Bovik “Automatic prediction of perceptual quality of multimediasignals—a survey,” in International Journal of Multimedia Tools and Applications, SpecialIssue on Survey Papers in Multimedia by World Experts, vol.51(1), pp.163-186, Jan.2011.
[232] A. K. Moorthy and A. C. Bovik,“Visual Quality Assessment Algorithms: What Does theFuture Hold?,” in International Journal of Multimedia Tools and Applications, Special Issue onSurvey Papers in Multimedia by World Experts, vol.51(2), pp.675-696, Feb.2011.
[233] M. Kampmann and J. Ostermann.“Automatic adaptation of a face model in a layered coderwith an object-based analysis-synthesis layer and a knowledge-based layer,” in SignalProcessing: Image Communications, vol.9(3), pp.201-220, Mar.1997.
[234] P. Eisert and B. Girod,“Model-based coding of facial image sequences at varying illuminationconditions,” in Proceedings of Image and Multidimensional Digital Signal ProcessingWorkshop, pp.119-122, July1998.
[235] A. M. Tekalp and J. Ostermann.“Face and2D mesh animation in MPEG-4,” in SignalProcessing: Image Communications. Special Issue on MPEG-4, vo.15(4), pp.387-421, Jan.2000.