基于第二代小波的图像与视频压缩的研究
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摘要
图像和视频是人类可以利用的最主要的信息载体。互联网的发展和多媒体的进步使得多媒体的各种新的应用和服务成为可能,尽管互联网的带宽和设备的存储容量都有所提高,但是数字化了的视频和图像信号的数据量之大是惊人的。数据压缩技术作为解决这一问题的有效途径,越来越受到大家的重视。
本文的滤波器采用Daubechies双正交滤波器,在图像压缩中,它获得了比正交小波更好的效果。具体采用的是Daub9/7小波变换。压缩编码采用了分层树集分裂算法(Set Partitioning In Hierarchical Trees SPIHT)以及3D-SPIHT算法。具体描述了嵌入式零树小波EZW(Embedded Zerotree Wavelet)算法与SPIHT算法在压缩中的应用,并且编码实现了SPIHT图像压缩与解压缩算法和3D-SPIHT视频压缩与解压缩算法。
将人眼视觉特性引入小波图像编码算法中,并对其进行了改进。本文使用了两种算法来引入人眼视觉特性,其核心是通过两个阈值T_1、T_2将小波图像分成的纹理块、平滑块、边缘块,并且对相应的小波系数赋予不同视觉权值。在第一种算法中,本文提出了新的广义高斯参数估计,引入了误差反向传播(Error BackPropagation BP)神经网络进行参数估计;在第二种算法中,本文将T_1规定为熵值的平均值。而T_2是一个较小的图像块方差。并在三种图像块分界处我们引入了模糊算法。使图像块的划分更加合理。两种算法都取得了较好的实验结果。
Image and video are among the most important information carriers for human being. Recently, the expansion of Internet and the development of multimedia technology have made it possible to implement new applications and services of multimedia. Although the Internet bandwidth and storage capability increased dramatically in the past decades, digitalized image and video signals still great challenges to our technology. As a feasible solution, data compression technology has been paid more and more attentions.
In this paper, we use Daubechies orthogonal filter to obtain better image compression results than orthogonal wavelet. In detail, we use the Daub 9/7 wavelet converter along with Set Partitioning In Hierarchical Trees (SPIHT) and 3D-SPIHT algorithms. Describe the application of Embedded Zerotree Wavelet (EZW) algorithm and SPIHT algorithm in real world compression tasks. In practice, we implemented the SPIHT image compression algorithm and the 3D-SPIHT video compressing and decompressing algorithm.
Introduce improved human visual characteristics into wavelet image coding algorithm. We use two algorithms to introduce human visual characteristics, the basic idea is to separate images into basic detailed or textured regions, smooth regions and strong regions by two threshold values T_1 and T_2 and then give different image parameter to corresponding wavelet coefficient. In the first algorithm, we introduce the BP neural network for the parameter estimation in Generalized Gaussian Distribution; In the second algorithm, we define T_1 the average value of all entropys and T_2 a smaller image deviation. We also use fuzzy algorithm in the dividing position of three different image blocks to make the division of image blocks more reasonable. Both of experiments show very inspiring results.
本文的滤波器采用Daubechies双正交滤波器,在图像压缩中,它获得了比正交小波更好的效果。具体采用的是Daub9/7小波变换。压缩编码采用了分层树集分裂算法(Set Partitioning In Hierarchical Trees SPIHT)以及3D-SPIHT算法。具体描述了嵌入式零树小波EZW(Embedded Zerotree Wavelet)算法与SPIHT算法在压缩中的应用,并且编码实现了SPIHT图像压缩与解压缩算法和3D-SPIHT视频压缩与解压缩算法。
将人眼视觉特性引入小波图像编码算法中,并对其进行了改进。本文使用了两种算法来引入人眼视觉特性,其核心是通过两个阈值T_1、T_2将小波图像分成的纹理块、平滑块、边缘块,并且对相应的小波系数赋予不同视觉权值。在第一种算法中,本文提出了新的广义高斯参数估计,引入了误差反向传播(Error BackPropagation BP)神经网络进行参数估计;在第二种算法中,本文将T_1规定为熵值的平均值。而T_2是一个较小的图像块方差。并在三种图像块分界处我们引入了模糊算法。使图像块的划分更加合理。两种算法都取得了较好的实验结果。
Image and video are among the most important information carriers for human being. Recently, the expansion of Internet and the development of multimedia technology have made it possible to implement new applications and services of multimedia. Although the Internet bandwidth and storage capability increased dramatically in the past decades, digitalized image and video signals still great challenges to our technology. As a feasible solution, data compression technology has been paid more and more attentions.
In this paper, we use Daubechies orthogonal filter to obtain better image compression results than orthogonal wavelet. In detail, we use the Daub 9/7 wavelet converter along with Set Partitioning In Hierarchical Trees (SPIHT) and 3D-SPIHT algorithms. Describe the application of Embedded Zerotree Wavelet (EZW) algorithm and SPIHT algorithm in real world compression tasks. In practice, we implemented the SPIHT image compression algorithm and the 3D-SPIHT video compressing and decompressing algorithm.
Introduce improved human visual characteristics into wavelet image coding algorithm. We use two algorithms to introduce human visual characteristics, the basic idea is to separate images into basic detailed or textured regions, smooth regions and strong regions by two threshold values T_1 and T_2 and then give different image parameter to corresponding wavelet coefficient. In the first algorithm, we introduce the BP neural network for the parameter estimation in Generalized Gaussian Distribution; In the second algorithm, we define T_1 the average value of all entropys and T_2 a smaller image deviation. We also use fuzzy algorithm in the dividing position of three different image blocks to make the division of image blocks more reasonable. Both of experiments show very inspiring results.
引文
[1]肖自美.图像信息理论与压缩编码技术.第一版,广州:中山大学出版社,2000.
[2]Khalid Sayood.Introduction to data compression.1~(st)Edition,San Francisco,California:Morgan Kaufmann Publishers,1996.
[3]Nasrabadi N M,King R A,Image coding using vector quantization:a review[J].IEEE Trans On Communacations,1988,36(8):957-971.
[4]Guan L,Kame IM.A vectordistribution model and an effective nearest neighbor or search method for image vector quantization[J].IEEE Trans On Image Processing,1997,6(12):1688-1691.
[5]Rinaldo R,Calvagno G.Hybrid Vector quantization for multiresolution image coding[J].IEEE Trans On Image Processing,1997,6(5):753-758.
[6]Rabbani M,Jones P.Digital Image Compression Techniques[J].SPIE,1991,1450:116-128.
[7]Witten I H,Neal R M,Cleary J G.Arithmetic Coding for Data Compression [J].Communications of the ACM,1987,30(6):520-540.
[8]Jacquin A E.Image coding based on a fractal theory of iterated contractive image transform actions[J].IEFE.Trans On Image Processiong,1992,1(1):18-30.
[9]Wohlberg B,Jager G de.Fractal dcoding performance for first-order Gauss-Markov models[J],Electronics Letters,1996,32:441-442.
[10]沈兰荪.图像编码与异步传输.第一版,北京,人民邮电出版社,1998.
[11]Hotter M,Thoma R.Image Segmentation Based on Object-oriented Mapping Parameter Estimation[J].Signal processing,1988,15(3):315-334.
[12]Daubechies I.Orthonormal bases of compactly supported wavelets[J].Communications on Pure and Applied mathematics,1988,41(11):909-996.
[13]Mallat S G.Multiresolution approximations and wavelet orthonormal bases of L~2(R).IEEE Trans.Amer.Math.Soc.,1989,315:69-87.
[14]Mallat S G.A theory for multiresolution signal decomposition:the wavelet representation[J].IEEE Trans.Pattern Analysis and machine Intelligence,1989,11(7):674-693.
[15]Daubechies I,Sweldens W.Factoring wavelet transforms into lifting steps.Journal of Fourier Analysis and Application,1998,4(3):245-267.
[16]Daubechies I.Ten Lectures on wavelets.Philadelphia:SIAM,1992.
[17]Sweldens W.She lifting scheme:A construction of second generation wavelet[J].SIAM Journal of Mathematical Analysis,1997,29(2):511-546.
[18]Sweldens W.The lifting scheme:A new philosophy in biorthogonal wavelet construction[A].Wavelet Applications in Signal and Image Processing Ⅲ[C],San Diego,CA,USA,1995,25(69):68-79.
[19]Sweldens W.The lifting scheme:A custom-design construction of biorthogonal wavelets[J].Applied and Computational Harmonic Analysis,1996,3(2)186-200.
[20]Sweldens W,Schroder P.Building your own wavelets at home[R].Technical report,Univ.of South Carolina,1995.
[21]Kim B J,Xiong Z,Pearlman W A.Low bit-rate scalable video coding with 3-D set partitioning in hierarchical trees(3-DSPIHT).IEEE Trans.CirSysVideo(10),2000,12(8):1374-1387.
[22]王新成.高级图像处理技术.第1版.北京:中国科学技术出版社,2001.
[23]阮秋琦.数字图像处理学.北京:电子工业出版社,1999.
[24]张兆礼,赵春晖,梅晓丹.现代图像处理技术及Matlab实现[M].北京:人民邮电出版社,2001.
[25]Donoho D L,Johnstone I M.Ideal spatial adaptation via wavelet shrinkage[J].Biometrika,1994,81:425-455.
[26]Woods J W,O' Nell S O.Subband coding of images[J].IEEE Trans Acoust Speech,and Signal Proc,1986,34(5):1278-1288.
[27]Shapiro J M.Embedded image coding using zerotree of wavelet coefficients[J].IEEE Trans.On Signal Processing,1993,41(12):3445-3462.
[28]Said A and Pearlman W A.A new fast and efficient image codec based on set partitioning in hierarchical trees.IEEETrans.Circuits Syst.VideoTechnol,1996,6(6):243-250.
[29]Taubman O.High performance scalable image compression with EBCOT [J].IEEE Trans.Image Processing,2000,9(7):1158-1170.
[30]Martucci S A,Sodagar I,Chiang T,Zhang Y.A zerotree wavelet video coder[J].IEEE Trans.on Circuits and Systems for Video Tech,1997,7(1):109-118.
[31]Marpe D,Cycon H L.Very low bit rate video coding using wavelet based techniques[J].IEEE Trans on Circuits and Systems for video Tech,1999,9(1):85-94.
[32]Vass J,Chai B B,Palaniappan K,Zhuang X.Significance-linked connected component analysis for low bit rate wavelet video coding[T].IEEE Trans on Circuits and Systems for Video Tech,1999,9(4):630-617.
[33]Taubman D,Zakbor A.Multirate 3-D subband coding of video[J].IEEE Trans on Image Processing,1994,3(5):572-588.
[34]Ohm J R.Three-dimensional subband coding with motion compensation [J].IEEE Trans on Image Processing,1994,3(5):559-571.
[35]Choi S J,Woods J W.Motion-compensated 3-D subband coding of video[J].IEEE Trans on Image Processing,1999,8(2):155-167.
[36]Boliek M,Christopoulos C,Majani E.3PEG 2000 Part Ⅰ Final Committee Draft Version 1.0[S].ISO/IEC JTC 1/SC 29/WG 1 N1646R,2000.
[37]Yang X,Ramchandram K.Scalable wavelet video coding using alisasing-reduced hierarchical motion compensation[J].IEEE Trans on Image Processing,2000,9(5):778-791.
[38]Ramos M G,Hemami S S,Tamburro M A.Psychovisually-based multiresolution image segmentation[A].Proceedings IEEE International Conference on Image Processing,Santa Barbara,1997,3:66-96.
[39]Meyer Y.Wavelets and Applications.Society for Industrial and Applied Mathematics,Philadelphia,1993.
[40]沈兰荪,卓立.小波编码与网络视频传输.北京:科学出版社,2004,85-91.
[41]Calderbank A R,Daubechies I,Sweldens W,Yeo B.Wavelet transforms that map integers to integers.Technical report,Department of Mathmatics,Princeton University,1996.
[42]曾凡永,谷东兵,宋正勋.基于小波变换的图像压缩方法中小波基的选取问题的探讨.光学精密机械学院学报,2000(6):26-30.
[43]周宁,汤晓军,孙飞等.提升小波快速算法及其在JPEG2000中的应用[J].中国有线电视,2002(18):6-10.
[44]Fernandez G,Periaswamy S,Sweldens W.LIFTPACK:a software package for wavelet transforms using lifting.Proc.SPIE 2825,Wavelet Application in Signal and Image Processing,1996,4:396-408.
[45]李宏亮,刘贵忠,侯兴松等.一种新的而为非线性提升小波变换方法[J].电子学报2003,31(1):21-24.
[46]全子一.数字视频图像处理.北京:电子工业出版社,2005.
[47]王向阳,杨红颖.基于多阈值与嵌入零树小波的图像压缩算法.通信学报,2001(12):16-21.
[48]陈毅松,孙正兴,张福炎.零树小波图像编码中的一种选择性系数扫描算法.计算机辅助设计与图形学学报,2001(9):19-24.
[49]雷英杰,华继学,周创明,肖正.图像工程与嵌入式零树小波图像编码.空军工程大学学报(自然科学版),2004(2):23-28.
[50]王向阳,杨红颖.基于人眼视觉特性的快速图像编码算法.软件学报,200314(11):1964-1970.
[51]Simoncelli E P.Modeling the joint statistics of images in the wavelet domain[C].Proc.SPIE,44th Annual Meeting,1999,38(13):188-195.
[52]韩力群.人工神经网络理论、设计及应用.北京:化学工业出版社,2002.
[2]Khalid Sayood.Introduction to data compression.1~(st)Edition,San Francisco,California:Morgan Kaufmann Publishers,1996.
[3]Nasrabadi N M,King R A,Image coding using vector quantization:a review[J].IEEE Trans On Communacations,1988,36(8):957-971.
[4]Guan L,Kame IM.A vectordistribution model and an effective nearest neighbor or search method for image vector quantization[J].IEEE Trans On Image Processing,1997,6(12):1688-1691.
[5]Rinaldo R,Calvagno G.Hybrid Vector quantization for multiresolution image coding[J].IEEE Trans On Image Processing,1997,6(5):753-758.
[6]Rabbani M,Jones P.Digital Image Compression Techniques[J].SPIE,1991,1450:116-128.
[7]Witten I H,Neal R M,Cleary J G.Arithmetic Coding for Data Compression [J].Communications of the ACM,1987,30(6):520-540.
[8]Jacquin A E.Image coding based on a fractal theory of iterated contractive image transform actions[J].IEFE.Trans On Image Processiong,1992,1(1):18-30.
[9]Wohlberg B,Jager G de.Fractal dcoding performance for first-order Gauss-Markov models[J],Electronics Letters,1996,32:441-442.
[10]沈兰荪.图像编码与异步传输.第一版,北京,人民邮电出版社,1998.
[11]Hotter M,Thoma R.Image Segmentation Based on Object-oriented Mapping Parameter Estimation[J].Signal processing,1988,15(3):315-334.
[12]Daubechies I.Orthonormal bases of compactly supported wavelets[J].Communications on Pure and Applied mathematics,1988,41(11):909-996.
[13]Mallat S G.Multiresolution approximations and wavelet orthonormal bases of L~2(R).IEEE Trans.Amer.Math.Soc.,1989,315:69-87.
[14]Mallat S G.A theory for multiresolution signal decomposition:the wavelet representation[J].IEEE Trans.Pattern Analysis and machine Intelligence,1989,11(7):674-693.
[15]Daubechies I,Sweldens W.Factoring wavelet transforms into lifting steps.Journal of Fourier Analysis and Application,1998,4(3):245-267.
[16]Daubechies I.Ten Lectures on wavelets.Philadelphia:SIAM,1992.
[17]Sweldens W.She lifting scheme:A construction of second generation wavelet[J].SIAM Journal of Mathematical Analysis,1997,29(2):511-546.
[18]Sweldens W.The lifting scheme:A new philosophy in biorthogonal wavelet construction[A].Wavelet Applications in Signal and Image Processing Ⅲ[C],San Diego,CA,USA,1995,25(69):68-79.
[19]Sweldens W.The lifting scheme:A custom-design construction of biorthogonal wavelets[J].Applied and Computational Harmonic Analysis,1996,3(2)186-200.
[20]Sweldens W,Schroder P.Building your own wavelets at home[R].Technical report,Univ.of South Carolina,1995.
[21]Kim B J,Xiong Z,Pearlman W A.Low bit-rate scalable video coding with 3-D set partitioning in hierarchical trees(3-DSPIHT).IEEE Trans.CirSysVideo(10),2000,12(8):1374-1387.
[22]王新成.高级图像处理技术.第1版.北京:中国科学技术出版社,2001.
[23]阮秋琦.数字图像处理学.北京:电子工业出版社,1999.
[24]张兆礼,赵春晖,梅晓丹.现代图像处理技术及Matlab实现[M].北京:人民邮电出版社,2001.
[25]Donoho D L,Johnstone I M.Ideal spatial adaptation via wavelet shrinkage[J].Biometrika,1994,81:425-455.
[26]Woods J W,O' Nell S O.Subband coding of images[J].IEEE Trans Acoust Speech,and Signal Proc,1986,34(5):1278-1288.
[27]Shapiro J M.Embedded image coding using zerotree of wavelet coefficients[J].IEEE Trans.On Signal Processing,1993,41(12):3445-3462.
[28]Said A and Pearlman W A.A new fast and efficient image codec based on set partitioning in hierarchical trees.IEEETrans.Circuits Syst.VideoTechnol,1996,6(6):243-250.
[29]Taubman O.High performance scalable image compression with EBCOT [J].IEEE Trans.Image Processing,2000,9(7):1158-1170.
[30]Martucci S A,Sodagar I,Chiang T,Zhang Y.A zerotree wavelet video coder[J].IEEE Trans.on Circuits and Systems for Video Tech,1997,7(1):109-118.
[31]Marpe D,Cycon H L.Very low bit rate video coding using wavelet based techniques[J].IEEE Trans on Circuits and Systems for video Tech,1999,9(1):85-94.
[32]Vass J,Chai B B,Palaniappan K,Zhuang X.Significance-linked connected component analysis for low bit rate wavelet video coding[T].IEEE Trans on Circuits and Systems for Video Tech,1999,9(4):630-617.
[33]Taubman D,Zakbor A.Multirate 3-D subband coding of video[J].IEEE Trans on Image Processing,1994,3(5):572-588.
[34]Ohm J R.Three-dimensional subband coding with motion compensation [J].IEEE Trans on Image Processing,1994,3(5):559-571.
[35]Choi S J,Woods J W.Motion-compensated 3-D subband coding of video[J].IEEE Trans on Image Processing,1999,8(2):155-167.
[36]Boliek M,Christopoulos C,Majani E.3PEG 2000 Part Ⅰ Final Committee Draft Version 1.0[S].ISO/IEC JTC 1/SC 29/WG 1 N1646R,2000.
[37]Yang X,Ramchandram K.Scalable wavelet video coding using alisasing-reduced hierarchical motion compensation[J].IEEE Trans on Image Processing,2000,9(5):778-791.
[38]Ramos M G,Hemami S S,Tamburro M A.Psychovisually-based multiresolution image segmentation[A].Proceedings IEEE International Conference on Image Processing,Santa Barbara,1997,3:66-96.
[39]Meyer Y.Wavelets and Applications.Society for Industrial and Applied Mathematics,Philadelphia,1993.
[40]沈兰荪,卓立.小波编码与网络视频传输.北京:科学出版社,2004,85-91.
[41]Calderbank A R,Daubechies I,Sweldens W,Yeo B.Wavelet transforms that map integers to integers.Technical report,Department of Mathmatics,Princeton University,1996.
[42]曾凡永,谷东兵,宋正勋.基于小波变换的图像压缩方法中小波基的选取问题的探讨.光学精密机械学院学报,2000(6):26-30.
[43]周宁,汤晓军,孙飞等.提升小波快速算法及其在JPEG2000中的应用[J].中国有线电视,2002(18):6-10.
[44]Fernandez G,Periaswamy S,Sweldens W.LIFTPACK:a software package for wavelet transforms using lifting.Proc.SPIE 2825,Wavelet Application in Signal and Image Processing,1996,4:396-408.
[45]李宏亮,刘贵忠,侯兴松等.一种新的而为非线性提升小波变换方法[J].电子学报2003,31(1):21-24.
[46]全子一.数字视频图像处理.北京:电子工业出版社,2005.
[47]王向阳,杨红颖.基于多阈值与嵌入零树小波的图像压缩算法.通信学报,2001(12):16-21.
[48]陈毅松,孙正兴,张福炎.零树小波图像编码中的一种选择性系数扫描算法.计算机辅助设计与图形学学报,2001(9):19-24.
[49]雷英杰,华继学,周创明,肖正.图像工程与嵌入式零树小波图像编码.空军工程大学学报(自然科学版),2004(2):23-28.
[50]王向阳,杨红颖.基于人眼视觉特性的快速图像编码算法.软件学报,200314(11):1964-1970.
[51]Simoncelli E P.Modeling the joint statistics of images in the wavelet domain[C].Proc.SPIE,44th Annual Meeting,1999,38(13):188-195.
[52]韩力群.人工神经网络理论、设计及应用.北京:化学工业出版社,2002.