多帧影像超分辨率复原重建关键技术研究
|
摘要
自从进入数字成像时代以来,在实际应用需求的驱动下,人们就没有停止过对获取更高分辨率影像的追求。采用影像超分辨率复原重建技术,就可以在不改变现有成像系统硬件的前提下,仅用软件算法的方式从多帧具有互补信息的低分辨率影像序列中重建出更高分辨率的影像。重建的结果不但可以改进影像的主观视觉效果,而且对影像的后续处理,如影像分割、特征提取、识别等各种研究应用都具有十分重要的意义。
本文以光学静态序列影像和视频流影像为主要研究对象,围绕多帧影像超分辨率复原重建的关键技术这一主题展开研究。主要研究工作如下：
(1)系统的总结、分析和比较了研究发展过程中形成的主要的超分辨率复原重建的理论和方法,并对其数学理论基础进行了分析讨论。针对现有研究对模型的适用条件和应用范围分析不够而导致模型的滥用和重建效果不稳定的问题,建立了基于形变与基于运动模糊这两种降质模型,并提出了基于不同降质模型的重建模型和重建方法框架。
(2)针对多帧运动模糊降质影像,提出序列帧运动模糊参数估计及多帧非线性复原重建的理论与算法。在这一框架下,对于任意方向的运动模糊参数估计问题,提出了基于二维倒频谱分析的算法来高精度的估计PSF的参数。为了减少重叠伪影,在详尽的分析产生重叠伪影的各种因素与重叠伪影间的相互关系的基础上,提出了预抑制伪影的基本思路和具体的实践算法。最后,提出了抑制重叠伪影的多帧非线性盲复原算法的理论框架和实践算法来提高运动模糊影像的分辨率。
(3)针对不以运动模糊为降质主要因素的多帧(视频流)影像,本文提出了基于Gauss-POCS模型的多帧序列的盲超分辨率复原重建的理论与算法。对该算法中的几个关键技术进行了研究：为了获取高精度的影像初始估计值,提出了保持边缘特性的双边滤波插值算法。对于运动估计问题,提出了全局与局部相结合的时空梯度迭代多帧亚像素运动估计算法。对于重建问题,以凸集投影作为理论基础,建立了多种约束算子集和相应的投影操作,改进了数据一致性约束,提出了一种重叠伪影的后抑制算法,并引入多帧联合去噪方法,最终建立了基于Gauss-POCS模型的盲超分辨率复原重建算法,获取主观视觉效果和客观评价指标均有较大提高的影像。
(4)有效的超分辨率算法的评价体系的建立一直是超分辨率研究领域的一个难度较大且富有挑战性的研究难点。为了研究这一问题,本文首先对现有的数字影像质量评价方法进行了全面的梳理,并使用多种指标对高斯模糊和加噪这两种超分辨率研究领域经常要处理的典型的降质类型进行了评价。然后针对超分辨率重建的评价现状进行了分析,明确了存在的问题。并以此为基础提出了超分辨率复原重建评价体系建立的思路和几个基本原则。最后在这一思路的指导下,提出了一种针对性强的有效的超分辨率重建中重叠伪影的后抑制和评价算法。
Since entering the digital imaging era, driven by actual demands, people are never stopping the pursuit for the higher resolution images. If using image super-resolution reconstruction technology, people can reconstruct a higher resolution image from low-resolution image sequence with complementary information by using some algorithms under the situation without changing the existing hardware. The reconstructive results not only can improve the subjective visual effect, but also are significant for the follow-up image processing, such as image segmentation, feature extraction, identification and so on.
In this paper, optical still image sequence and video streaming are used as main object of study. We focus on the key technologies of multi-frame image SR reconstruction. Main research works are shown as follow. (1) Systematically summarize, analyze and compare the main SR theories and methods which formed in the development of the research field. And its mathematical basis are analyzed and discussed. To solve the problem that abusing the reconstructive models and unstable reconstructive results which is caused by the inadequate analysis about the application conditions and application range of the models, two different models are established that one is based on warping and the other is based on the motion blur, and proposed a reconstruction model and framework based on different degraded models.
(2) For multi-frame motion blur degraded images, a theory and algorithm is proposed for multi-frame estimation for motion-blur parameters and multi-frame nonlinear reconstruction. Under this framework, for solving the problem that parameter estimation for any direction of motion-blur, an algorithm is proposed that using two-dimensional cepstrum analysis to estimate the parameters of PSF. In order to reduce wraparound artifact, we proposed the basic idea of how to suppress wraparound artifact and specific algorithm to do it based on detailed analysis of the relationship between wraparound artifact and various factors producing it. Finally, for improving the resolution of motion-blur images, a blind multi-frame non-linear reconstruction algorithm and framework is proposed.
(3) For multi-frames (video streaming) that not main degraded by motion blur, the theory and algorithm of blind multi-frame SR reconstruction based on Gauss-POCS model is proposed. Several key technologies have been studied as follow. For obtained high-precision initial estimates, a bilateral filter interpolation algorithm is proposed which can maintain edge features well. For motion estimation problem, we proposed multi-frame subpixel motion-estimation algorithms which use spatio-temporal gradient iterative and combine global model and local model. For solving reconstruction problem, we use POCS as the theoretical basis to establish a variety of constraints and the corresponding projection operations. Data consistency constraints have been improved. A post-suppressed algorithm for wraparound artifact is proposed. Multi-frame joint denoising method is introduced. Finally, we establish a blind SR reconstruction algorithm based on Gauss-POCS model to obtain the image that subjective visual effects and objective assessment are greatly improved.
(4) Establishment of efficient evaluation system for SR algorithm has always been a difficult and challenging research area in SR research. For research this problem, firstly the existing digital image quality evaluation methods are sorted out. And a variety of indicators are used to evaluate Gaussian blur and Gaussian noise which are two typical degraded types in SR research field. Then, current evaluation situation of SR reconstruction has been analyzed and existing problems has been identified. We proposed some ideas and a few basic principles that establish evaluation system for SR reconstruction based on above analysis. Finally, an effective post-suppressed algorithm and assessment index for wraparound artifact which is produced by SR reconstruction is proposed.
本文以光学静态序列影像和视频流影像为主要研究对象,围绕多帧影像超分辨率复原重建的关键技术这一主题展开研究。主要研究工作如下：
(1)系统的总结、分析和比较了研究发展过程中形成的主要的超分辨率复原重建的理论和方法,并对其数学理论基础进行了分析讨论。针对现有研究对模型的适用条件和应用范围分析不够而导致模型的滥用和重建效果不稳定的问题,建立了基于形变与基于运动模糊这两种降质模型,并提出了基于不同降质模型的重建模型和重建方法框架。
(2)针对多帧运动模糊降质影像,提出序列帧运动模糊参数估计及多帧非线性复原重建的理论与算法。在这一框架下,对于任意方向的运动模糊参数估计问题,提出了基于二维倒频谱分析的算法来高精度的估计PSF的参数。为了减少重叠伪影,在详尽的分析产生重叠伪影的各种因素与重叠伪影间的相互关系的基础上,提出了预抑制伪影的基本思路和具体的实践算法。最后,提出了抑制重叠伪影的多帧非线性盲复原算法的理论框架和实践算法来提高运动模糊影像的分辨率。
(3)针对不以运动模糊为降质主要因素的多帧(视频流)影像,本文提出了基于Gauss-POCS模型的多帧序列的盲超分辨率复原重建的理论与算法。对该算法中的几个关键技术进行了研究：为了获取高精度的影像初始估计值,提出了保持边缘特性的双边滤波插值算法。对于运动估计问题,提出了全局与局部相结合的时空梯度迭代多帧亚像素运动估计算法。对于重建问题,以凸集投影作为理论基础,建立了多种约束算子集和相应的投影操作,改进了数据一致性约束,提出了一种重叠伪影的后抑制算法,并引入多帧联合去噪方法,最终建立了基于Gauss-POCS模型的盲超分辨率复原重建算法,获取主观视觉效果和客观评价指标均有较大提高的影像。
(4)有效的超分辨率算法的评价体系的建立一直是超分辨率研究领域的一个难度较大且富有挑战性的研究难点。为了研究这一问题,本文首先对现有的数字影像质量评价方法进行了全面的梳理,并使用多种指标对高斯模糊和加噪这两种超分辨率研究领域经常要处理的典型的降质类型进行了评价。然后针对超分辨率重建的评价现状进行了分析,明确了存在的问题。并以此为基础提出了超分辨率复原重建评价体系建立的思路和几个基本原则。最后在这一思路的指导下,提出了一种针对性强的有效的超分辨率重建中重叠伪影的后抑制和评价算法。
Since entering the digital imaging era, driven by actual demands, people are never stopping the pursuit for the higher resolution images. If using image super-resolution reconstruction technology, people can reconstruct a higher resolution image from low-resolution image sequence with complementary information by using some algorithms under the situation without changing the existing hardware. The reconstructive results not only can improve the subjective visual effect, but also are significant for the follow-up image processing, such as image segmentation, feature extraction, identification and so on.
In this paper, optical still image sequence and video streaming are used as main object of study. We focus on the key technologies of multi-frame image SR reconstruction. Main research works are shown as follow. (1) Systematically summarize, analyze and compare the main SR theories and methods which formed in the development of the research field. And its mathematical basis are analyzed and discussed. To solve the problem that abusing the reconstructive models and unstable reconstructive results which is caused by the inadequate analysis about the application conditions and application range of the models, two different models are established that one is based on warping and the other is based on the motion blur, and proposed a reconstruction model and framework based on different degraded models.
(2) For multi-frame motion blur degraded images, a theory and algorithm is proposed for multi-frame estimation for motion-blur parameters and multi-frame nonlinear reconstruction. Under this framework, for solving the problem that parameter estimation for any direction of motion-blur, an algorithm is proposed that using two-dimensional cepstrum analysis to estimate the parameters of PSF. In order to reduce wraparound artifact, we proposed the basic idea of how to suppress wraparound artifact and specific algorithm to do it based on detailed analysis of the relationship between wraparound artifact and various factors producing it. Finally, for improving the resolution of motion-blur images, a blind multi-frame non-linear reconstruction algorithm and framework is proposed.
(3) For multi-frames (video streaming) that not main degraded by motion blur, the theory and algorithm of blind multi-frame SR reconstruction based on Gauss-POCS model is proposed. Several key technologies have been studied as follow. For obtained high-precision initial estimates, a bilateral filter interpolation algorithm is proposed which can maintain edge features well. For motion estimation problem, we proposed multi-frame subpixel motion-estimation algorithms which use spatio-temporal gradient iterative and combine global model and local model. For solving reconstruction problem, we use POCS as the theoretical basis to establish a variety of constraints and the corresponding projection operations. Data consistency constraints have been improved. A post-suppressed algorithm for wraparound artifact is proposed. Multi-frame joint denoising method is introduced. Finally, we establish a blind SR reconstruction algorithm based on Gauss-POCS model to obtain the image that subjective visual effects and objective assessment are greatly improved.
(4) Establishment of efficient evaluation system for SR algorithm has always been a difficult and challenging research area in SR research. For research this problem, firstly the existing digital image quality evaluation methods are sorted out. And a variety of indicators are used to evaluate Gaussian blur and Gaussian noise which are two typical degraded types in SR research field. Then, current evaluation situation of SR reconstruction has been analyzed and existing problems has been identified. We proposed some ideas and a few basic principles that establish evaluation system for SR reconstruction based on above analysis. Finally, an effective post-suppressed algorithm and assessment index for wraparound artifact which is produced by SR reconstruction is proposed.
引文
[1]CCD(Charge-coupled device), http://en.wikipedia.org/wiki/Charge-coupled_device,3 Mar 2010
[2]晏磊,赵红颖,罗妙宣,数字成像基础及系统技术,北京：电子工业出版社,2007,389页
[3]CMOS(Active pixel sensor), http://en.wikipedia.org/wiki/Active_pixel_sensor#Comparison_to_CCDs,20 Mar 2010
[4]Chaudhuri S, Joshi M V, Motion-Free Super-Resolution, New York:Springer-Verlag New York, Inc.,2005,
[5]Image resolution, http://en.wikipedia.org/wiki/Image_resolution#Spectral_resolution,19 Mar 2010
[6]Park S C, Park M K, Kang M G, Super-resolution image reconstruction:A technical overview, Ieee Signal Processing Magazine,2003,20 (3):21-36
[7]Komatsu T, Aizawa K, Igarashi Tet al., Signal-processing based method for acquiring very high resolution images with multiple cameras and its theoretical analysis, IEE Proceedings, Part I:Communications, Speech and Vision,1993,140 (1):19-25
[8]Driggers R, Krapels K, Young S, The meaning of super-resolution, Infrared Imaging Systems:Design, Analysis, Modeling, and Testing XVI, March 30,2005-April 1,2005, Orlando, FL, United states:SPIE,2005,103-106
[9]Choi E, Choi J, Kang M G, Super-resolution approach to overcome physical limitations of imaging sensors:An overview, International Journal Of Imaging Systems And Technology, 2004,14 (2):36-46
[10]吴斌,吴亚东,张红英,基于变分偏微分方程的图像复原技术,北京：北京大学出版社,2008,212页
[11]那彦,焦李成,基于多分辨分析理论的图像融合方法,西安：西安电子科技大学出版社,2007,250页
[12]沈焕锋,场景变化条件下的影像超分辨率重建技术研究,博士论文,武汉大学,2007
[13]Li F, Jia X P, Fraser D, Superresolution Reconstruction of Multispectral Data for Improved Image Classification, IEEE Geoscience and Remote Sensing Letters,2009,6 (4):689-693
[14]Elbakary M, Alam M, Superresolution construction of multispectral imagery based on local enhancement, IEEE Geoscience and Remote Sensing Letters,2008,5 (2):276-279
[15]Elbakary M I, Alam M S, Superresolution Image Reconstruction Using Panchromatic and Multispectral Image Fusion-art. no.7072IN, Optics and Photonics for Information Processing Ⅱ,2008,7072:N721-N721
[16]Akgun T, Altunbasak Y, Mersereau R M, Superresolution reconstruction of hyperspectral images,2004 IEEE International Conference on Acoustics,Speech,and Signal Processing, 2004, vol.3:497-500
[17]Mianji F A, Zhang Y, Hosseinipanah M, A Classification Enhancement in Hyperspectral Imagery Using Superresolution Technique, ICSP:2008 9TH International Conference on Signal Processing,2008, vol.1-5:998-1001
[18]范冲,三线阵影像超分辨率重建,博士论文,中南大学,2007
[19]苑玮琦,柯利,白云,生物特征识别技术,北京：科学出版社,2009
[20]Gunturk B K, Batur A U, Altunbasak Yet al., Eigenface-domain super-resolution for face recognition, Ieee Transactions On Image Processing,2003,12 (5):597-606
[21]Chakrabarti A, Rajagopalan A N, Chellappa R, Super-resolution of face images using kernel PCA-based prior, IEEE transactions on multimedia,2007,9 (4):888-892
[22]Jia K, Gong S, Generalized face super-resolution,2008,
[23]Park S W, Savvides M, Super-Resolution of Face Images, Biometrics: Theory, Methods, and Applications,2009,:295
[24]Cui J L, Wang Y H, Huang J Zet al., An iris image synthesis method based on PCA and super-resolution, Proceedings of the 17TH International Conference on Pattern Recognition, 2004, vol.4:471-474
[25]Jiao L, Wu Y, Wu Get al., Anatomy of a multicamera video surveillance system, Multimedia Systems,2004,10 (2):144-163
[26]Qin F Q, He X H, Chen W Let al., Video superresolution reconstruction based on subpixel registration and iterative back projection, Journal Of Electronic Imaging,2009,18 (1)
[27]Sroubek F, Flusser J, Sorel M, Superresolution and blind deconvolution of video,19TH International Conference on Pattern Recogntion,2008, vol.1-6:168-171
[28]Young S S, Driggers R G, Superresolution image reconstruction from a sequence of aliased imagery, Applied Optics,2006,45 (21):5073-5085
[29]Bowen O, Bouganis C S, Real-time Image Super Resolution Using an FPGA,2008 Internation Conference on Field Progammable and Logic Applications,2008, vol.1-2: 89-94
[30]Martins B, Forchhammer S, A unified approach to restoration, deinterlacing and resolution enhancement in decoding MPEG-2 video, Ieee Transactions On Circuits And Systems For Video Technology,2002,12 (9):803-811
[31]Akyildiz IF, Melodia T, Chowdhury K R, A survey on wireless multimedia sensor networks, Computer Networks,2007,51 (4):921-960
[32]Xie W, Lin L, Qin Q, Motion-based blind super-resolution approach to overcome spatial limitation of camera sensor network,2009 International Conference on Digital Image Processing, Bangkok, Thailand:IEEE Computer Society,2009,45-49
[33]Segall C A, Molina R, Katsaggelos A K, High-resolution images from low-resolution compressed video, Ieee Signal Processing Magazine,2003,20 (3):37-48
[34]Dugad R, Ahuja N, A fast scheme for image size change in the compressed domain, Ieee Transactions On Circuits And Systems For Video Technology,2001,11 (4):461-474
[35]Krapels K, Driggers R G, Jacobs Eet al., Characteristics of infrared imaging systems that benefit from superresolution reconstruction, Applied Optics,2007,46 (21):4594-4603
[36]Zalevsky Z, Shamir N, Mendlovic D, Geometrical superresolution in infrared sensor: experimental verification, Optical Engineering,2004,43 (6):1401-1406
[37]Li J, Sheng Y L, Sevigny Tet al., Wavelet domain superresolution reconstruction of infrared image sequences, Sensor Fusion:Architectures,Algorithms and Applications V, 2001,4385:108-116
[38]Chadwick A, Superresolution for high-frequency radar, let Radar Sonar and Navigation, 2007,1(6):431-436
[39]Quinquis A, Radoi E, Totir F C, Some radar imagery results using superresolution techniques, Ieee Transactions On Antennas And Propagation,2004,52 (5):1230-1244
[40]Willett R, Nowak R, Wavelet-based superresolution in astronomy, Astronomical Data Analysis Software and Systems XIII,2004,314:107-116
[41]Greenspan H, Super-Resolution in Medical Imaging, Computer Journal,2009,52 (1): 43-63
[42]Farsiu S, Robinson M D, Elad Met al., Fast and robust multiframe super resolution, Ieee Transactions On Image Processing,2004,13 (10):1327-1344
[43]Farsiu S, Robinson D, Elad Met al., Advances and challenges in super-resolution, International Journal Of Imaging Systems And Technology,2004,14 (2):47-57
[44]Farsiu S, Elad M, Milanfar P, Multiframe demosaicing and super-resolution of color images, Ieee Transactions On Image Processing,2006,15 (1):141-159
[45]Farsiu S, MDSP Resolution Enhancement Software User's Manual,2004,
[46]谭兵,邢帅,徐青等,SPOT5超模式数据处理技术研究,遥感技术与应用,2004,(04)
[47]孙涛,多约束条件遥感影像超分辨重建逆问题研究,博士后研究工作报告,武汉大学,2008
[48]Super CCD, http://en.wikipedia.org/wiki/Super_CCD,18 April 2010
[49]History of Super CCD, http://www.fujifilm.com/products/digital_cameras/exr/history/, 2010
[50]EXR Technology:High Resolution, http://www.fujifilm.com/products/digital_cameras/exr/features/index.html,2010
[51]Tsai R Y, Huang T S, Multiframe image restoration and registration, Advances in Computer Vision and Image Processing,1984,1 (2):317-339
[52]Vandewalle P, Suesstrunk S, Vetterli M, A frequency domain approach to registration of aliased images with application to super-resolution, Eurasip Journal on Applied Signal Processing,2006,
[53]李金宗,杨学峰,李冬冬,新颖的频域图像超分辨重建方法,计算机应用,2009,(11)
[54]Ur H, Gross D, Improved resolution from subpixel shifted pictures, CVGIP: Graphical Models and Image Processing,1992,54 (2):181-186
[55]Irani M, Peleg S, Improving resolution by image registration, CVGIP: Graph. Models Image Process.,1991,53 (3):231-239
[56]Irani M, Peleg S, Motion analysis for image enhancement: Resolution, occlusion, and transparency, Journal Of Visual Communication And Image Representation,1993,4 (4): 1993-12
[57]Qin F Q, He X H, Chen W Let al., Video superresolution reconstruction based on subpixel registration and iterative back projection, Journal Of Electronic Imaging,2009,18 (0130071)
[58]Stark H, Oskoui P, High-resolution image recovery from image-plane arrays, using convex projections, Journal of the Optical Society of America A,1989,6(11):1715-1726
[59]Tekalp A M, Ozkan M K, Sezan M I, High-resolution image reconstruction from lower-resolution image sequences and space-varying image restoration, Acoustics, Speech, and Signal Processing,1992. IEEE International Conference on, San Francisco,CA,USA, 1992,169-172
[60]Patti A J, Ibrahim Sezan M, Murat Tekalp A, High-resolution image reconstruction from a low-resolution image sequence in the presence of time-varying motion blur, Image Processing, ICIP-94, IEEE International Conference, Austin,1994,343-347
[61]Patti A J, Altunbasak Y, Artifact reduction for set theoretic super resolution image reconstruction with edge adaptive constraints and higher-order interpolants, Image Processing, IEEE Transactions on,2001,10 (1):179-186
[62]Jung S W, Kim T H, Ko S J, A Novel Multiple Image Deblurring Technique Using Fuzzy Projection onto Convex Sets, Ieee Signal Processing Letters,2009,16 (1-3):192-195
[63]Chong F, Jianjun Z, Jianya Get al., POCS Super-Resolution Sequence Image Reconstruction Based on Improvement Approach of Keren Registration Method, Intelligent Systems Design and Applications,2006., Jinan,2006,333-337
[64]Xie W, Sun T, Liu Get al., Super-resolution image reconstruction from a sequence of motion images, SPIE Fifth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR 2007), Wuhan, China:SPIE,2007
[65]Pickup L C, Capel D P, Roberts S Jet al., Bayesian Methods for Image Super-Resolution, Computer Journal,2009,52 (1):101-113
[66]Isakson S W, Bayesian superresolution, Ph.D. thesis, University of California, Santa Barbara,2001
[67]Schultz R R, Stevenson R L, Improved definition image expansion, Acoustics, Speech, and Signal Processing,1992. ICASSP-92.,1992 IEEE International Conference on, San Francisco,CA,USA,1992,173-176 vol.3
[68]Cheeseman P, Kanefsky B, Kraft Ret al., Super-Resolved Surface Reconstruction From Multiple Images, NASA Ames Research Center, Moffett Field,1994,
[69]He Y, Yap K H, Chen Let al., A soft MAP framework for blind super-resolution image reconstruction, Image And Vision Computing,2009,27 (4):364-373
[70]Elad M, Feuer A, Superresolution restoration of an image sequence:Adaptive filtering approach, Ieee Transactions On Image Processing,1999,8 (3):387-395
[71]Bose N K, Lertrattanapanich S, Advances in Wavelet Superresolution, Orlando, Florida, USA,2001,
[72]Bose N K, Chappalli M B, A Second Generation Wavelet Framework for Superresolution with Noise Filtering, International J. on Imaging Science and Technology (Special Issue on High Resolution Image Reconstruction),2004,14 (2):84-89
[73]Chappali M B, Bose N K, Simultaneous Noise Filtering and Super-Resolution With Second-Generation Wavelets, Ieee Signal Processing Letters,2005,12(11):772-775
[74]Bose N K, Lertrattanapanich S, Chappalli M B, Superresolution with second generation wavelets, Signal Processing,2004,19 (5):387-391
[75]Ahuja N A, Bose N K, Generalized sampling theorem for wavelet based superresolution, Atlanta,GA,USA,2006,
[76]Lertrattanapanich S, Bose N K, High resolution image formation from low resolution frames using Delaunay triangulation, Ieee Transactions On Image Processing,2002,11 (12):1427-1441
[77]Lertrattanapanich S, Bose N K, HR image from multiframes by Delaunay triangulation:A synopsis, International Conference on Image Processing (ICIP'02), Rochester, NY, United states:Institute of Electrical and Electronics Engineers Computer Society,2002, Ⅱ/869-II/872
[78]Liu J, Yan H, Sun J, Regularization Super-Resolution with Inaccurate Image Registration, Ieice Transactions On Information And Systems,2009, E92D (1):59-68
[79]Yap K H, He Y, Tian Y Set al., A Nonlinear L-1-Norm Approach for Joint Image Registration and Super-Resolution, Ieee Signal Processing Letters,2009,16 (11):981-984
[80]Baboulaz L, Dragotti P L, Exact Feature Extraction Using Finite Rate of Innovation Principles With an Application to Image Super-Resolution, Ieee Transactions On Image Processing,2009,18 (2):281-298
[81]He Y, Yap K H, Chen Let al., Blind super-resolution image reconstruction using a maximum a posteriori estimation, Proceedings International Conference on Image Processing, Vols 1-7, New York: IEEE,2006,1729-1732
[82]Chen Y X, Luo Y P, Hu D C, A general approach to blind image super-resolution using a PDE framework, Visual Communications and Image Processing 2005, Pts 1-4, Bellingham: SPIE-INT SOC Optical Engineering,2005,1819-1830
[83]Sroubek F, Flusser J, Resolution enhancement via probabilistic deconvolution of multiple degraded images, Pattern Recognition Letters,2006,27 (4):287-293
[84]Yang H D, Li X, Chen K Xet al., Blind deconvolution algorithm for spectrogram super-resolution restoration, Spectroscopy And Spectral Analysis,2007,27 (7):1249-1253
[85]Xie W, Zhang F, Chen Het al., Blind super-resolution image reconstruction based on POCS model,2009 International Conference on Measuring Technology and Mechatronics Automation (ICMTMA 2009), Zhangjiajie, Hunan, China: IEEE Computer Society,2009, 437-440
[86]Babacan S D, Molina R, Katsaggelos A K, Variational Bayesian Blind Deconvolution Using a Total Variation Prior, Ieee Transactions On Image Processing,2009,18(1):12-26
[87]Altunbasak Y, Patti A J, Mersereau R M, Super-resolution still and video reconstruction from MPEG-coded video, Ieee Transactions On Circuits And Systems For Video Technology,2002,12 (4):217-226
[88]Gunturk B K, Altunbasak Y, Mersereau R M, Super-resolution reconstruction of compressed video using transform-domain statistics, Ieee Transactions On Image Processing,2004,13 (1):33-43
[89]Wang C, Xue P, Lin W S, Improved super-resolution reconstruction from video, Ieee Transactions On Circuits And Systems For Video Technology,2006,16 (11):1411-1422
[90]Fishbain B, Ideses I A, Shabat Get al., Superresolution in color videos acquired through turbulent media, Optics Letters,2009,34 (5):587-589
[91]Ni K S, Nguyen T Q, Color image superresolution based on a stochastic combinational classification-regression algorithm,2007 IEEE International Conference on Image Processing, New York:IEEE,2007,653-656
[92]Shroff H, Galbraith C G, Galbraith J Aet al., Dual-color superresolution imaging of genetically expressed probes within individual adhesion complexes, Proceedings Of The National Academy Of Sciences Of The United States Of America,2007,104 (51): 20308-20313
[93]Rajan D, Chaudhuri S, An MRF-based approach to generation of super-resolution images from blurred observations, Journal Of Mathematical Imaging And Vision,2002,16 (1): 5-15
[94]Lin Z C, He J F, Tang X Oet al., Limits of learning-based superresolution algorithms, International Journal Of Computer Vision,2008,80 (3):406-420
[95]袁建华,超分辨率重建中若干问题的研究,博士论文,中国科学院研究生院(电子学研究所),2006
[96]韩玉兵,图像及视频序列的超分辨率重建,博士论文,东南大学,2006
[97]肖建平,图像超分辨率算法与硬件实现研究,博士论文,华中科技大学,2006
[98]宋锐,视频和图像序列的超分辨率重建技术研究,博士论文,西安电子科技大学,2009
[99]谭兵,多帧图像空间分辨率增强技术研究,博士论文,解放军信息工程大学,2004
[100]张艳,空间域超分辨率图像重建技术研究,博士论文,解放军信息工程大学,2007
[101]徐青等编著,遥感影像融合与分辨率增强技术,北京：科学出版社,2007
[102]Shen H, Zhang L, Huang Bet al., A MAP approach for joint motion estimation, segmentation, and super resolution, Ieee Transactions On Image Processing,2007,16 (2): 479-490
[103]沈焕锋,李平湘,张良培,一种自适应正则MAP超分辨率重建方法,武汉大学学报：信息科学版,2006,31(011)：949-952
[104]Shen H F, Ng M K, Li P Xet al., Super-Resolution Reconstruction Algorithm To MODIS Remote Sensing Images, Computer Journal,2009,52 (1):90-100
[105]谭兵,徐青,邢帅等,小波超分辨率重建算法及其在SPOT影像中的应用,测绘学报,2004,33 (3)
[106]van Ouwerkerk J D, Image super-resolution survey, Image And Vision Computing,2006, 24 (10):1039-1052
[107]Watanabe K, Iwai Y, Haga Tet al., A Fast Algorithm of Video Super-Resolution Using Dimensionality Reduction by DCT and Example Selection,2008,1174-1178
[108]Katsaggelos A K, Molina R, Mateos J, Super resolution of images and video,2007,
[109]Tom B C, Katsaggelos A K, Reconstruction of a high-resolution image by simultaneous registration, restoration, and interpolation of low-resolution images,:Citeseer,1995, 539-542
[110]Bregman L M, Determination of a common point of convex sets by the method of successive projection, Akademiia Nauk Sssr,1965,162:487-490
[111]余英林,谢胜利,蔡汉添,信号处理新方法导论,北京：清华大学出版社,2004
[112]Jiang M, Zhang Z, Review on POCS algorithms for image reconstruction, Computerized Tomography Theory and Applications,2003,12 (1):51-55
[113]邹谋炎,反卷积和信号复原,北京：国防工业出版社,2001
[114]Lertrattanapanich S, Superresolution from degraded image sequence using spatial tessellations and wavelets, Ph.D. thesis, The Pennsylvania State University,2003
[115]Point spread function, http://en.wikipedia.org/wiki/Point_spread_function,11 Mar 2010
[116]谭耀麟,图像信息系统原理,北京：清华大学出版社,2006
[117]Elad M, Feuer A, Restoration of a single superresolution image from several blurred, noisy, and undersampled measured images, Image Processing, IEEE Transactions on,1997,6 (12):1646-1658
[118]Keller J, Inverse problems, American Mathematical Monthly,1976,83 (2):107-118
[119]Hadamard J, Lectures on the Cauchy Problem in Linear Partial Differential Equations, New Haven, CT, USA:Yale University Press,1923,
[120]李兴华,高分辨力空间摄影相机像移补偿控制技术研究,博士论文,中国科学院长春光学精密机械与物理研究所,2000
[121]颜昌翔,王家骐,航相机像移补偿计算的坐标变换方法,光学精密工程,2000, (03)
[122]吴宏圣,TDICCD全景航空相机像移补偿研究,硕士论文,中国科学院研究生院(长春光学精密机械与物理研究所),2003
[123]Ben-Ezra M, Nayar S K, Motion-based motion deblurring, Ieee Transactions On Pattern Analysis And Machine Intelligence,2004,26 (6):689-698
[124]刘微,运动模糊图像恢复算法的研究与实现,博士论文,中国科学院研究生院(长春光学精密机械与物理研究所),2006
[125]Lagendijk R L, Tekalp A M, Biemond J, Maximum likelihood image and blur identification. A unifying approach, Optical Engineering,1990,29 (5):422-435
[126]陈前荣,陆启生,成礼智,运动模糊图像的运动模糊方向鉴别,国防科技大学学报,2004, (01)
[127]Cannon M, Blind Deconvolution of Spatially Invariant Image Blurs with Phase, IEEE Transactions on Acoustics, Speech, and Signal Processing,1976, ASSP-24 (1):58-63
[128]王晓红,赵荣椿,匀速直线运动模糊的PSF之估计,计算机应用,2001, (09)
[129]王晓红,赵荣椿,任意方向运动模糊的消除,中国图象图形学报,2000, (06)
[130]Yitzhaky Y, Mor I, Lantzman Aet al., Direct method for restoration of motion-blurred images, Journal of the Optical Society of America A:Optics and Image Science, and Vision, 1998,15(6):1512-1512
[131]Bogert B P, Healy M J R, Tukey J W, The Quefrency Alanysis of Time Series for Echoes: Cepstrum, Psuedo-Autocovariance, Cross-cepstrum and Saphe Cracking, NewYork,USA, 1963,209-243
[132]Oppenheim A V, Schafer R W, From frequency to quefrency: A history of the Cepstrum, Ieee Signal Processing Magazine,2004,21 (5):95-99
[133]Gonzalez R C, Woods. R E, Digital image processing,:Prentice Hall,2008,954页
[134]Pratt W K, Digital image processing:PIKS inside,:Wiley,2001,735页
[135]Richardson W H, Bayesian-Based Iterative Method of Image Restoration, Journal of the Optical Society of America,1972,62 (1):55-59
[136]Lucy L B, An iterative technique for the rectification of observed distributions, Astronomical Journal,1974,79:745
[137]Disk, http://users.soe.ucsc.edu/-milanfar/software/sr-datasets.html,2010
[138]Tomasi C, Manduchi R, Bilateral filtering for gray and color images,6TH International Conference on Computer Vision, Bombay,India,1998,839-846
[139]Durand F, Dorsey J, Fast bilateral filtering for the display of high-dynamic-range images, Acm Transactions On Graphics,2002,21 (3):257-266
[140]Paris S, Durand F, A Fast Approximation of the Bilateral Filter Using a Signal Processing Approach, International Journal Of Computer Vision,2009,81 (1):24-52
[141]姜三平,基于小波变换的图像降噪,北京：国防工业出版社,2009,128页
[142]Keren D, Peleg S, Brada R, Image sequence enhancement using sub-pixel displacements, Ann Arbor,MI,1988,742-746
[143]Wagner R S, Waagen D, Cassabaum M, Image super-resolution for improved automatic target recognition, Automatic Target Recognition XIV, Orlando,FL,USA,2004,188-196
[144]Goodman J W, Introduction to Fourier optics,:Roberts and Company Publishers,2005,491 pages
[145]Capel D, Image mosaicing and super-resolution,:Springer,2004,218 pages
[146]Nguyen N, Golub G, Milanfar P, Blind restoration/superresolution with generalized cross-validation using Gauss-type quadrature rules, United States,1999,1257-1261
[147]Hardie R C, Barnard K J, Armstrong E E, Joint MAP registration and high-resolution image estimation using a sequence of undersampled images, Image Processing, IEEE Transactions on,1997,6 (12):1621-1633
[148]Cristobal G, Gil E, Roubek Fet al., Superresolution imaging: A survey of current techniques, San Diego, CA, United states: SPIE,2008, The International Society for Optical Engineering (SPIE)
[149]Pham T Q, van Vliet L J, Schutte K, Robust fusion of irregularly sampled data using adaptive normalized convolution, Eurasip Journal on Applied Signal Processing,2006, (83268)
[150]周景超,戴汝为,肖柏华,图像质量评价研究综述,计算机科学,2008, (07)
[151]VQEG, http://www.its.bldrdoc.gov/vqeg/,2010
[152]LIVE Image Quality Assessment Database, http://live.ece.utexas.edu/research/quality/subjective.htm,6 Feb 2009
[153]Wang Z, Bovik A C, Simoncelli H Ret al., Image quality assessment:From error visibility to structural similarity, Ieee Transactions On Image Processing,2004,13 (4):600-612
[154]Zhou W, Bovik A C, A universal image quality index, Signal Processing Letters, IEEE, 2002,9 (3):81-84
[155]Sheikh H R, Bovik A C, Cormack L, No-reference quality assessment using natural scene statistics: JPEG2000, Image Processing, IEEE Transactions on,2005,14 (11):1918-1927
[156]Wang Z, Bovik A C, Mean Squared Error: Love It or Leave It? A new look at signal fidelity measures, Ieee Signal Processing Magazine,2009,26 (1):98-117
[157]Zhou W, Xinli S, Spatial Pooling Strategies for Perceptual Image Quality Assessment, Image Processing,2006 IEEE International Conference on, Atlanta,GA,USA,2006, 2945-2948
[158]Piella G, Heijmans H, A new quality metric for image fusion,2003 International Conference on Image Processing, Barcelona,Spain,2003, Ⅲ-173-6
[159]Alattar A M, Lin E T, Celik M U, Digital watermarking of low bit-rate advanced simple profile MPEG-4 compressed video, Circuits and Systems for Video Technology, IEEE Transactions on,2003,13 (8):787-800
[160]Toet A, Lucassen M P, A new universal colour image fidelity metric, Displays,2003,24 (4-5):197-207
[161]Snidaro L, Foresti G L, A multi-camera approach to sensor evaluation in video surveillance, Image Processing,IEEE International Conference on, Genova,Italy,2005,Ⅰ-1101-4
[162]Christophe E, Leger D, Mailhes C, Quality criteria benchmark for hyperspectral imagery, Ieee Transactions On Geoscience And Remote Sensing,2005,43 (9):2103-2114
[163]Kim S P, Su W Y, Recursive high-resolution reconstruction of blurred multiframe images, Acoustics, Speech, and Signal Processing,1991. ICASSP-91.,1991 International Conference on, Toronto,Canada,1991,2977-2980
[164]Saito T, Komatsu T, Aizawa K, A signal-processing based method for acquiring very high resolution images with multiple cameras and its theoretical analysis, International Conference on Image Processing and its Applications, Manchester,United Kingdom,1992, 365-368
[165]Toronto N, Morse B S, Seppi Ket al., Super-resolution via recapture and Bayesian effect modeling, Computer Vision and Pattern Recognition 2009, IEEE Conference on, Miami,FL,USA,2009,2388-2395
[166]Joshi M V, Chaudhuri S, Panuganti R, A learning-based method for image super-resolution from zoomed observations, Systems, Man, and Cybernetics, Part B:Cybernetics, IEEE Transactions on,2005,35 (3):527-537
[167]Liu F, Wang J, Zhu Set al., Visual-Quality Optimizing Super Resolution, Computer Graphics Forum,2009,28 (1):127-140
[168]Reibman A R, Bell R M, Gray S, Quality assessment for super-resolution image enhancement, Image Processing,2006 IEEE International Conference on, Atlanta,GA,USA, 2006,2017-2020
[2]晏磊,赵红颖,罗妙宣,数字成像基础及系统技术,北京：电子工业出版社,2007,389页
[3]CMOS(Active pixel sensor), http://en.wikipedia.org/wiki/Active_pixel_sensor#Comparison_to_CCDs,20 Mar 2010
[4]Chaudhuri S, Joshi M V, Motion-Free Super-Resolution, New York:Springer-Verlag New York, Inc.,2005,
[5]Image resolution, http://en.wikipedia.org/wiki/Image_resolution#Spectral_resolution,19 Mar 2010
[6]Park S C, Park M K, Kang M G, Super-resolution image reconstruction:A technical overview, Ieee Signal Processing Magazine,2003,20 (3):21-36
[7]Komatsu T, Aizawa K, Igarashi Tet al., Signal-processing based method for acquiring very high resolution images with multiple cameras and its theoretical analysis, IEE Proceedings, Part I:Communications, Speech and Vision,1993,140 (1):19-25
[8]Driggers R, Krapels K, Young S, The meaning of super-resolution, Infrared Imaging Systems:Design, Analysis, Modeling, and Testing XVI, March 30,2005-April 1,2005, Orlando, FL, United states:SPIE,2005,103-106
[9]Choi E, Choi J, Kang M G, Super-resolution approach to overcome physical limitations of imaging sensors:An overview, International Journal Of Imaging Systems And Technology, 2004,14 (2):36-46
[10]吴斌,吴亚东,张红英,基于变分偏微分方程的图像复原技术,北京：北京大学出版社,2008,212页
[11]那彦,焦李成,基于多分辨分析理论的图像融合方法,西安：西安电子科技大学出版社,2007,250页
[12]沈焕锋,场景变化条件下的影像超分辨率重建技术研究,博士论文,武汉大学,2007
[13]Li F, Jia X P, Fraser D, Superresolution Reconstruction of Multispectral Data for Improved Image Classification, IEEE Geoscience and Remote Sensing Letters,2009,6 (4):689-693
[14]Elbakary M, Alam M, Superresolution construction of multispectral imagery based on local enhancement, IEEE Geoscience and Remote Sensing Letters,2008,5 (2):276-279
[15]Elbakary M I, Alam M S, Superresolution Image Reconstruction Using Panchromatic and Multispectral Image Fusion-art. no.7072IN, Optics and Photonics for Information Processing Ⅱ,2008,7072:N721-N721
[16]Akgun T, Altunbasak Y, Mersereau R M, Superresolution reconstruction of hyperspectral images,2004 IEEE International Conference on Acoustics,Speech,and Signal Processing, 2004, vol.3:497-500
[17]Mianji F A, Zhang Y, Hosseinipanah M, A Classification Enhancement in Hyperspectral Imagery Using Superresolution Technique, ICSP:2008 9TH International Conference on Signal Processing,2008, vol.1-5:998-1001
[18]范冲,三线阵影像超分辨率重建,博士论文,中南大学,2007
[19]苑玮琦,柯利,白云,生物特征识别技术,北京：科学出版社,2009
[20]Gunturk B K, Batur A U, Altunbasak Yet al., Eigenface-domain super-resolution for face recognition, Ieee Transactions On Image Processing,2003,12 (5):597-606
[21]Chakrabarti A, Rajagopalan A N, Chellappa R, Super-resolution of face images using kernel PCA-based prior, IEEE transactions on multimedia,2007,9 (4):888-892
[22]Jia K, Gong S, Generalized face super-resolution,2008,
[23]Park S W, Savvides M, Super-Resolution of Face Images, Biometrics: Theory, Methods, and Applications,2009,:295
[24]Cui J L, Wang Y H, Huang J Zet al., An iris image synthesis method based on PCA and super-resolution, Proceedings of the 17TH International Conference on Pattern Recognition, 2004, vol.4:471-474
[25]Jiao L, Wu Y, Wu Get al., Anatomy of a multicamera video surveillance system, Multimedia Systems,2004,10 (2):144-163
[26]Qin F Q, He X H, Chen W Let al., Video superresolution reconstruction based on subpixel registration and iterative back projection, Journal Of Electronic Imaging,2009,18 (1)
[27]Sroubek F, Flusser J, Sorel M, Superresolution and blind deconvolution of video,19TH International Conference on Pattern Recogntion,2008, vol.1-6:168-171
[28]Young S S, Driggers R G, Superresolution image reconstruction from a sequence of aliased imagery, Applied Optics,2006,45 (21):5073-5085
[29]Bowen O, Bouganis C S, Real-time Image Super Resolution Using an FPGA,2008 Internation Conference on Field Progammable and Logic Applications,2008, vol.1-2: 89-94
[30]Martins B, Forchhammer S, A unified approach to restoration, deinterlacing and resolution enhancement in decoding MPEG-2 video, Ieee Transactions On Circuits And Systems For Video Technology,2002,12 (9):803-811
[31]Akyildiz IF, Melodia T, Chowdhury K R, A survey on wireless multimedia sensor networks, Computer Networks,2007,51 (4):921-960
[32]Xie W, Lin L, Qin Q, Motion-based blind super-resolution approach to overcome spatial limitation of camera sensor network,2009 International Conference on Digital Image Processing, Bangkok, Thailand:IEEE Computer Society,2009,45-49
[33]Segall C A, Molina R, Katsaggelos A K, High-resolution images from low-resolution compressed video, Ieee Signal Processing Magazine,2003,20 (3):37-48
[34]Dugad R, Ahuja N, A fast scheme for image size change in the compressed domain, Ieee Transactions On Circuits And Systems For Video Technology,2001,11 (4):461-474
[35]Krapels K, Driggers R G, Jacobs Eet al., Characteristics of infrared imaging systems that benefit from superresolution reconstruction, Applied Optics,2007,46 (21):4594-4603
[36]Zalevsky Z, Shamir N, Mendlovic D, Geometrical superresolution in infrared sensor: experimental verification, Optical Engineering,2004,43 (6):1401-1406
[37]Li J, Sheng Y L, Sevigny Tet al., Wavelet domain superresolution reconstruction of infrared image sequences, Sensor Fusion:Architectures,Algorithms and Applications V, 2001,4385:108-116
[38]Chadwick A, Superresolution for high-frequency radar, let Radar Sonar and Navigation, 2007,1(6):431-436
[39]Quinquis A, Radoi E, Totir F C, Some radar imagery results using superresolution techniques, Ieee Transactions On Antennas And Propagation,2004,52 (5):1230-1244
[40]Willett R, Nowak R, Wavelet-based superresolution in astronomy, Astronomical Data Analysis Software and Systems XIII,2004,314:107-116
[41]Greenspan H, Super-Resolution in Medical Imaging, Computer Journal,2009,52 (1): 43-63
[42]Farsiu S, Robinson M D, Elad Met al., Fast and robust multiframe super resolution, Ieee Transactions On Image Processing,2004,13 (10):1327-1344
[43]Farsiu S, Robinson D, Elad Met al., Advances and challenges in super-resolution, International Journal Of Imaging Systems And Technology,2004,14 (2):47-57
[44]Farsiu S, Elad M, Milanfar P, Multiframe demosaicing and super-resolution of color images, Ieee Transactions On Image Processing,2006,15 (1):141-159
[45]Farsiu S, MDSP Resolution Enhancement Software User's Manual,2004,
[46]谭兵,邢帅,徐青等,SPOT5超模式数据处理技术研究,遥感技术与应用,2004,(04)
[47]孙涛,多约束条件遥感影像超分辨重建逆问题研究,博士后研究工作报告,武汉大学,2008
[48]Super CCD, http://en.wikipedia.org/wiki/Super_CCD,18 April 2010
[49]History of Super CCD, http://www.fujifilm.com/products/digital_cameras/exr/history/, 2010
[50]EXR Technology:High Resolution, http://www.fujifilm.com/products/digital_cameras/exr/features/index.html,2010
[51]Tsai R Y, Huang T S, Multiframe image restoration and registration, Advances in Computer Vision and Image Processing,1984,1 (2):317-339
[52]Vandewalle P, Suesstrunk S, Vetterli M, A frequency domain approach to registration of aliased images with application to super-resolution, Eurasip Journal on Applied Signal Processing,2006,
[53]李金宗,杨学峰,李冬冬,新颖的频域图像超分辨重建方法,计算机应用,2009,(11)
[54]Ur H, Gross D, Improved resolution from subpixel shifted pictures, CVGIP: Graphical Models and Image Processing,1992,54 (2):181-186
[55]Irani M, Peleg S, Improving resolution by image registration, CVGIP: Graph. Models Image Process.,1991,53 (3):231-239
[56]Irani M, Peleg S, Motion analysis for image enhancement: Resolution, occlusion, and transparency, Journal Of Visual Communication And Image Representation,1993,4 (4): 1993-12
[57]Qin F Q, He X H, Chen W Let al., Video superresolution reconstruction based on subpixel registration and iterative back projection, Journal Of Electronic Imaging,2009,18 (0130071)
[58]Stark H, Oskoui P, High-resolution image recovery from image-plane arrays, using convex projections, Journal of the Optical Society of America A,1989,6(11):1715-1726
[59]Tekalp A M, Ozkan M K, Sezan M I, High-resolution image reconstruction from lower-resolution image sequences and space-varying image restoration, Acoustics, Speech, and Signal Processing,1992. IEEE International Conference on, San Francisco,CA,USA, 1992,169-172
[60]Patti A J, Ibrahim Sezan M, Murat Tekalp A, High-resolution image reconstruction from a low-resolution image sequence in the presence of time-varying motion blur, Image Processing, ICIP-94, IEEE International Conference, Austin,1994,343-347
[61]Patti A J, Altunbasak Y, Artifact reduction for set theoretic super resolution image reconstruction with edge adaptive constraints and higher-order interpolants, Image Processing, IEEE Transactions on,2001,10 (1):179-186
[62]Jung S W, Kim T H, Ko S J, A Novel Multiple Image Deblurring Technique Using Fuzzy Projection onto Convex Sets, Ieee Signal Processing Letters,2009,16 (1-3):192-195
[63]Chong F, Jianjun Z, Jianya Get al., POCS Super-Resolution Sequence Image Reconstruction Based on Improvement Approach of Keren Registration Method, Intelligent Systems Design and Applications,2006., Jinan,2006,333-337
[64]Xie W, Sun T, Liu Get al., Super-resolution image reconstruction from a sequence of motion images, SPIE Fifth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR 2007), Wuhan, China:SPIE,2007
[65]Pickup L C, Capel D P, Roberts S Jet al., Bayesian Methods for Image Super-Resolution, Computer Journal,2009,52 (1):101-113
[66]Isakson S W, Bayesian superresolution, Ph.D. thesis, University of California, Santa Barbara,2001
[67]Schultz R R, Stevenson R L, Improved definition image expansion, Acoustics, Speech, and Signal Processing,1992. ICASSP-92.,1992 IEEE International Conference on, San Francisco,CA,USA,1992,173-176 vol.3
[68]Cheeseman P, Kanefsky B, Kraft Ret al., Super-Resolved Surface Reconstruction From Multiple Images, NASA Ames Research Center, Moffett Field,1994,
[69]He Y, Yap K H, Chen Let al., A soft MAP framework for blind super-resolution image reconstruction, Image And Vision Computing,2009,27 (4):364-373
[70]Elad M, Feuer A, Superresolution restoration of an image sequence:Adaptive filtering approach, Ieee Transactions On Image Processing,1999,8 (3):387-395
[71]Bose N K, Lertrattanapanich S, Advances in Wavelet Superresolution, Orlando, Florida, USA,2001,
[72]Bose N K, Chappalli M B, A Second Generation Wavelet Framework for Superresolution with Noise Filtering, International J. on Imaging Science and Technology (Special Issue on High Resolution Image Reconstruction),2004,14 (2):84-89
[73]Chappali M B, Bose N K, Simultaneous Noise Filtering and Super-Resolution With Second-Generation Wavelets, Ieee Signal Processing Letters,2005,12(11):772-775
[74]Bose N K, Lertrattanapanich S, Chappalli M B, Superresolution with second generation wavelets, Signal Processing,2004,19 (5):387-391
[75]Ahuja N A, Bose N K, Generalized sampling theorem for wavelet based superresolution, Atlanta,GA,USA,2006,
[76]Lertrattanapanich S, Bose N K, High resolution image formation from low resolution frames using Delaunay triangulation, Ieee Transactions On Image Processing,2002,11 (12):1427-1441
[77]Lertrattanapanich S, Bose N K, HR image from multiframes by Delaunay triangulation:A synopsis, International Conference on Image Processing (ICIP'02), Rochester, NY, United states:Institute of Electrical and Electronics Engineers Computer Society,2002, Ⅱ/869-II/872
[78]Liu J, Yan H, Sun J, Regularization Super-Resolution with Inaccurate Image Registration, Ieice Transactions On Information And Systems,2009, E92D (1):59-68
[79]Yap K H, He Y, Tian Y Set al., A Nonlinear L-1-Norm Approach for Joint Image Registration and Super-Resolution, Ieee Signal Processing Letters,2009,16 (11):981-984
[80]Baboulaz L, Dragotti P L, Exact Feature Extraction Using Finite Rate of Innovation Principles With an Application to Image Super-Resolution, Ieee Transactions On Image Processing,2009,18 (2):281-298
[81]He Y, Yap K H, Chen Let al., Blind super-resolution image reconstruction using a maximum a posteriori estimation, Proceedings International Conference on Image Processing, Vols 1-7, New York: IEEE,2006,1729-1732
[82]Chen Y X, Luo Y P, Hu D C, A general approach to blind image super-resolution using a PDE framework, Visual Communications and Image Processing 2005, Pts 1-4, Bellingham: SPIE-INT SOC Optical Engineering,2005,1819-1830
[83]Sroubek F, Flusser J, Resolution enhancement via probabilistic deconvolution of multiple degraded images, Pattern Recognition Letters,2006,27 (4):287-293
[84]Yang H D, Li X, Chen K Xet al., Blind deconvolution algorithm for spectrogram super-resolution restoration, Spectroscopy And Spectral Analysis,2007,27 (7):1249-1253
[85]Xie W, Zhang F, Chen Het al., Blind super-resolution image reconstruction based on POCS model,2009 International Conference on Measuring Technology and Mechatronics Automation (ICMTMA 2009), Zhangjiajie, Hunan, China: IEEE Computer Society,2009, 437-440
[86]Babacan S D, Molina R, Katsaggelos A K, Variational Bayesian Blind Deconvolution Using a Total Variation Prior, Ieee Transactions On Image Processing,2009,18(1):12-26
[87]Altunbasak Y, Patti A J, Mersereau R M, Super-resolution still and video reconstruction from MPEG-coded video, Ieee Transactions On Circuits And Systems For Video Technology,2002,12 (4):217-226
[88]Gunturk B K, Altunbasak Y, Mersereau R M, Super-resolution reconstruction of compressed video using transform-domain statistics, Ieee Transactions On Image Processing,2004,13 (1):33-43
[89]Wang C, Xue P, Lin W S, Improved super-resolution reconstruction from video, Ieee Transactions On Circuits And Systems For Video Technology,2006,16 (11):1411-1422
[90]Fishbain B, Ideses I A, Shabat Get al., Superresolution in color videos acquired through turbulent media, Optics Letters,2009,34 (5):587-589
[91]Ni K S, Nguyen T Q, Color image superresolution based on a stochastic combinational classification-regression algorithm,2007 IEEE International Conference on Image Processing, New York:IEEE,2007,653-656
[92]Shroff H, Galbraith C G, Galbraith J Aet al., Dual-color superresolution imaging of genetically expressed probes within individual adhesion complexes, Proceedings Of The National Academy Of Sciences Of The United States Of America,2007,104 (51): 20308-20313
[93]Rajan D, Chaudhuri S, An MRF-based approach to generation of super-resolution images from blurred observations, Journal Of Mathematical Imaging And Vision,2002,16 (1): 5-15
[94]Lin Z C, He J F, Tang X Oet al., Limits of learning-based superresolution algorithms, International Journal Of Computer Vision,2008,80 (3):406-420
[95]袁建华,超分辨率重建中若干问题的研究,博士论文,中国科学院研究生院(电子学研究所),2006
[96]韩玉兵,图像及视频序列的超分辨率重建,博士论文,东南大学,2006
[97]肖建平,图像超分辨率算法与硬件实现研究,博士论文,华中科技大学,2006
[98]宋锐,视频和图像序列的超分辨率重建技术研究,博士论文,西安电子科技大学,2009
[99]谭兵,多帧图像空间分辨率增强技术研究,博士论文,解放军信息工程大学,2004
[100]张艳,空间域超分辨率图像重建技术研究,博士论文,解放军信息工程大学,2007
[101]徐青等编著,遥感影像融合与分辨率增强技术,北京：科学出版社,2007
[102]Shen H, Zhang L, Huang Bet al., A MAP approach for joint motion estimation, segmentation, and super resolution, Ieee Transactions On Image Processing,2007,16 (2): 479-490
[103]沈焕锋,李平湘,张良培,一种自适应正则MAP超分辨率重建方法,武汉大学学报：信息科学版,2006,31(011)：949-952
[104]Shen H F, Ng M K, Li P Xet al., Super-Resolution Reconstruction Algorithm To MODIS Remote Sensing Images, Computer Journal,2009,52 (1):90-100
[105]谭兵,徐青,邢帅等,小波超分辨率重建算法及其在SPOT影像中的应用,测绘学报,2004,33 (3)
[106]van Ouwerkerk J D, Image super-resolution survey, Image And Vision Computing,2006, 24 (10):1039-1052
[107]Watanabe K, Iwai Y, Haga Tet al., A Fast Algorithm of Video Super-Resolution Using Dimensionality Reduction by DCT and Example Selection,2008,1174-1178
[108]Katsaggelos A K, Molina R, Mateos J, Super resolution of images and video,2007,
[109]Tom B C, Katsaggelos A K, Reconstruction of a high-resolution image by simultaneous registration, restoration, and interpolation of low-resolution images,:Citeseer,1995, 539-542
[110]Bregman L M, Determination of a common point of convex sets by the method of successive projection, Akademiia Nauk Sssr,1965,162:487-490
[111]余英林,谢胜利,蔡汉添,信号处理新方法导论,北京：清华大学出版社,2004
[112]Jiang M, Zhang Z, Review on POCS algorithms for image reconstruction, Computerized Tomography Theory and Applications,2003,12 (1):51-55
[113]邹谋炎,反卷积和信号复原,北京：国防工业出版社,2001
[114]Lertrattanapanich S, Superresolution from degraded image sequence using spatial tessellations and wavelets, Ph.D. thesis, The Pennsylvania State University,2003
[115]Point spread function, http://en.wikipedia.org/wiki/Point_spread_function,11 Mar 2010
[116]谭耀麟,图像信息系统原理,北京：清华大学出版社,2006
[117]Elad M, Feuer A, Restoration of a single superresolution image from several blurred, noisy, and undersampled measured images, Image Processing, IEEE Transactions on,1997,6 (12):1646-1658
[118]Keller J, Inverse problems, American Mathematical Monthly,1976,83 (2):107-118
[119]Hadamard J, Lectures on the Cauchy Problem in Linear Partial Differential Equations, New Haven, CT, USA:Yale University Press,1923,
[120]李兴华,高分辨力空间摄影相机像移补偿控制技术研究,博士论文,中国科学院长春光学精密机械与物理研究所,2000
[121]颜昌翔,王家骐,航相机像移补偿计算的坐标变换方法,光学精密工程,2000, (03)
[122]吴宏圣,TDICCD全景航空相机像移补偿研究,硕士论文,中国科学院研究生院(长春光学精密机械与物理研究所),2003
[123]Ben-Ezra M, Nayar S K, Motion-based motion deblurring, Ieee Transactions On Pattern Analysis And Machine Intelligence,2004,26 (6):689-698
[124]刘微,运动模糊图像恢复算法的研究与实现,博士论文,中国科学院研究生院(长春光学精密机械与物理研究所),2006
[125]Lagendijk R L, Tekalp A M, Biemond J, Maximum likelihood image and blur identification. A unifying approach, Optical Engineering,1990,29 (5):422-435
[126]陈前荣,陆启生,成礼智,运动模糊图像的运动模糊方向鉴别,国防科技大学学报,2004, (01)
[127]Cannon M, Blind Deconvolution of Spatially Invariant Image Blurs with Phase, IEEE Transactions on Acoustics, Speech, and Signal Processing,1976, ASSP-24 (1):58-63
[128]王晓红,赵荣椿,匀速直线运动模糊的PSF之估计,计算机应用,2001, (09)
[129]王晓红,赵荣椿,任意方向运动模糊的消除,中国图象图形学报,2000, (06)
[130]Yitzhaky Y, Mor I, Lantzman Aet al., Direct method for restoration of motion-blurred images, Journal of the Optical Society of America A:Optics and Image Science, and Vision, 1998,15(6):1512-1512
[131]Bogert B P, Healy M J R, Tukey J W, The Quefrency Alanysis of Time Series for Echoes: Cepstrum, Psuedo-Autocovariance, Cross-cepstrum and Saphe Cracking, NewYork,USA, 1963,209-243
[132]Oppenheim A V, Schafer R W, From frequency to quefrency: A history of the Cepstrum, Ieee Signal Processing Magazine,2004,21 (5):95-99
[133]Gonzalez R C, Woods. R E, Digital image processing,:Prentice Hall,2008,954页
[134]Pratt W K, Digital image processing:PIKS inside,:Wiley,2001,735页
[135]Richardson W H, Bayesian-Based Iterative Method of Image Restoration, Journal of the Optical Society of America,1972,62 (1):55-59
[136]Lucy L B, An iterative technique for the rectification of observed distributions, Astronomical Journal,1974,79:745
[137]Disk, http://users.soe.ucsc.edu/-milanfar/software/sr-datasets.html,2010
[138]Tomasi C, Manduchi R, Bilateral filtering for gray and color images,6TH International Conference on Computer Vision, Bombay,India,1998,839-846
[139]Durand F, Dorsey J, Fast bilateral filtering for the display of high-dynamic-range images, Acm Transactions On Graphics,2002,21 (3):257-266
[140]Paris S, Durand F, A Fast Approximation of the Bilateral Filter Using a Signal Processing Approach, International Journal Of Computer Vision,2009,81 (1):24-52
[141]姜三平,基于小波变换的图像降噪,北京：国防工业出版社,2009,128页
[142]Keren D, Peleg S, Brada R, Image sequence enhancement using sub-pixel displacements, Ann Arbor,MI,1988,742-746
[143]Wagner R S, Waagen D, Cassabaum M, Image super-resolution for improved automatic target recognition, Automatic Target Recognition XIV, Orlando,FL,USA,2004,188-196
[144]Goodman J W, Introduction to Fourier optics,:Roberts and Company Publishers,2005,491 pages
[145]Capel D, Image mosaicing and super-resolution,:Springer,2004,218 pages
[146]Nguyen N, Golub G, Milanfar P, Blind restoration/superresolution with generalized cross-validation using Gauss-type quadrature rules, United States,1999,1257-1261
[147]Hardie R C, Barnard K J, Armstrong E E, Joint MAP registration and high-resolution image estimation using a sequence of undersampled images, Image Processing, IEEE Transactions on,1997,6 (12):1621-1633
[148]Cristobal G, Gil E, Roubek Fet al., Superresolution imaging: A survey of current techniques, San Diego, CA, United states: SPIE,2008, The International Society for Optical Engineering (SPIE)
[149]Pham T Q, van Vliet L J, Schutte K, Robust fusion of irregularly sampled data using adaptive normalized convolution, Eurasip Journal on Applied Signal Processing,2006, (83268)
[150]周景超,戴汝为,肖柏华,图像质量评价研究综述,计算机科学,2008, (07)
[151]VQEG, http://www.its.bldrdoc.gov/vqeg/,2010
[152]LIVE Image Quality Assessment Database, http://live.ece.utexas.edu/research/quality/subjective.htm,6 Feb 2009
[153]Wang Z, Bovik A C, Simoncelli H Ret al., Image quality assessment:From error visibility to structural similarity, Ieee Transactions On Image Processing,2004,13 (4):600-612
[154]Zhou W, Bovik A C, A universal image quality index, Signal Processing Letters, IEEE, 2002,9 (3):81-84
[155]Sheikh H R, Bovik A C, Cormack L, No-reference quality assessment using natural scene statistics: JPEG2000, Image Processing, IEEE Transactions on,2005,14 (11):1918-1927
[156]Wang Z, Bovik A C, Mean Squared Error: Love It or Leave It? A new look at signal fidelity measures, Ieee Signal Processing Magazine,2009,26 (1):98-117
[157]Zhou W, Xinli S, Spatial Pooling Strategies for Perceptual Image Quality Assessment, Image Processing,2006 IEEE International Conference on, Atlanta,GA,USA,2006, 2945-2948
[158]Piella G, Heijmans H, A new quality metric for image fusion,2003 International Conference on Image Processing, Barcelona,Spain,2003, Ⅲ-173-6
[159]Alattar A M, Lin E T, Celik M U, Digital watermarking of low bit-rate advanced simple profile MPEG-4 compressed video, Circuits and Systems for Video Technology, IEEE Transactions on,2003,13 (8):787-800
[160]Toet A, Lucassen M P, A new universal colour image fidelity metric, Displays,2003,24 (4-5):197-207
[161]Snidaro L, Foresti G L, A multi-camera approach to sensor evaluation in video surveillance, Image Processing,IEEE International Conference on, Genova,Italy,2005,Ⅰ-1101-4
[162]Christophe E, Leger D, Mailhes C, Quality criteria benchmark for hyperspectral imagery, Ieee Transactions On Geoscience And Remote Sensing,2005,43 (9):2103-2114
[163]Kim S P, Su W Y, Recursive high-resolution reconstruction of blurred multiframe images, Acoustics, Speech, and Signal Processing,1991. ICASSP-91.,1991 International Conference on, Toronto,Canada,1991,2977-2980
[164]Saito T, Komatsu T, Aizawa K, A signal-processing based method for acquiring very high resolution images with multiple cameras and its theoretical analysis, International Conference on Image Processing and its Applications, Manchester,United Kingdom,1992, 365-368
[165]Toronto N, Morse B S, Seppi Ket al., Super-resolution via recapture and Bayesian effect modeling, Computer Vision and Pattern Recognition 2009, IEEE Conference on, Miami,FL,USA,2009,2388-2395
[166]Joshi M V, Chaudhuri S, Panuganti R, A learning-based method for image super-resolution from zoomed observations, Systems, Man, and Cybernetics, Part B:Cybernetics, IEEE Transactions on,2005,35 (3):527-537
[167]Liu F, Wang J, Zhu Set al., Visual-Quality Optimizing Super Resolution, Computer Graphics Forum,2009,28 (1):127-140
[168]Reibman A R, Bell R M, Gray S, Quality assessment for super-resolution image enhancement, Image Processing,2006 IEEE International Conference on, Atlanta,GA,USA, 2006,2017-2020