图像超分辨率重建问题研究
|
摘要
图像超分辨率重建是指从一幅或多幅低分辨率、低质量图像中产生高分辨率、高质量图像的数字信号处理技术。本文针对光学图像,研究了图像超分辨率重建问题。其研究的重点放在对图像超分辨率重建方法研究的分析与设计上,内容涉及到单幅图像到单幅图像的超分辨率重建,多幅图像到单幅图像的超分辨率重建、图像超分辨率重建的关键技术以及超分辨率评价准则的建立。主要研究工作包括以下方面：
(1)针对光学图像,从光学系统成像机理出发,发展了一种较为广泛的图像退化模型,指明了其中的造成图像分辨率降低的若干关键环节。同时,针对单幅图像到单幅图像的超分辨率重建问题,与图像复原问题相联系,提出了一种基于分层思想的图像超分辨率重建方法；在算法的设计过程中,将问题分解为若干问题,分别解之,在算法的实施过程中,提出了一种级联模板运算的方法,该方法回避了巨型矩阵乘法运算,较之传统的做法,算法的复杂度降低。
(2)针对多幅图像到单幅图像的超分辨率重建问题,研究了种基于概率论与集合论相集成的MAP/POCS混合方法,推导了实现该算法的方程,并将单幅图像重建算法的剥离方法应用到算法的具体实现中。
(3)针对传统的基于插值的图像超分辨率重建方法,在讨论和分析其优点和不足之处后,提出了一种基于子像素位移B样条插值的图像超分辨率重建方法,该方法将原用于单幅图像到单幅图像超分辨率重建的B样条插值技术引入到多幅图像到单幅图像超分辨率重建中,利用相互间存在子像素位移的多幅图像上的附加信息来提高分辨率。
(4)针对超分辨率重建过程中的若干关键问题,进行了深入的探讨,内容包括降晰函数的辨识、巨型方程组的解法以及自由运动的超分辨率重建等许多问题,对于降晰函数的估计就信噪比的高低讨论了频域法和误差参数估计法,对于方程组的计算提出了一种近似算子的有效预处理方式。
(5)初步探讨了图像超分辨率重建的评价准则问题,提出了剖密度曲线CD图像超分辨率重建的评价准则。并就评价准则问题提出了一些想法,作为开问题出现在论文中。
Image super-resolution reconstruction is the image processing technology to produce the image of the high-quality, high-resolution from the low quality, low-resolution in the single or multi-images. In the thesis, it is elaborated and the algorithms involved are focused on. Briefly speaking, the main work includes one image reconstruction from one image and several images (or image sequence), image sequence reconstruction from image sequence, the criterion for super-resolution, etc.The research is listed as follows.
First, the research background and the situation at home and abroad of the art are reviewed, with its presence in various fields of military and civilian application indicated. Furthermore, an overview of current methods employed to the SR reconstruction is given, the fundamental skill, difficult issue and future development are all discussed. Based on these, the relation and the difference between the SR reconstruction and the technologies related are further such as image restoration, resolution, image enhancement and blur, etc. clarified.
For the problem of one image super resolution reconstruction from one image, a novel method is developed. A flaking method is suggested in the design of the algorithm; a more efficient approach is presented in the implement of the algorithm, the method avoids the operations of huge matrix. Compared with the traditional method, it is efficient and low complexity.
As for the problem of one image super resolution reconstruction from one image, we develop a novel method. A flaking method is suggested in the design of the algorithm; a more efficient approach is presented in the implement of the algorithm, our method runaround the operations of huge matrix. So, comparing our method with traditional method, the former is efficient and low complexity.
As far as super-resolution construction from image sequence to single image is concerned, a new B-spline interpolation method based on the image sequence is proposed by using the additional data in the sequence of existing mobile-related sub-pixel to improve the resolution. Besides, a integrated MAP/POCS hybrid approach is also proposed based on probability theory and the collection methods, with the derivation of the equations of the algorithm presented and spin-off of a single image reconstruction algorithm method applied to the specific algorithm implementation.
Some key problems including the model of image degradation, the estimation of blurring function and the method for big size equation system in super resolution reconstruction are studied deeply. For the high and low SNR, the frequency method and error-parameter estimative method are discussed; for the big size system, an effect pre-process method is considered.
In the last part of the thesis, some methods for the criterion of super-resolution are presented and the method of profile density curve is introduced. We also proposed some ideas as open problems for this problem.
(1)针对光学图像,从光学系统成像机理出发,发展了一种较为广泛的图像退化模型,指明了其中的造成图像分辨率降低的若干关键环节。同时,针对单幅图像到单幅图像的超分辨率重建问题,与图像复原问题相联系,提出了一种基于分层思想的图像超分辨率重建方法；在算法的设计过程中,将问题分解为若干问题,分别解之,在算法的实施过程中,提出了一种级联模板运算的方法,该方法回避了巨型矩阵乘法运算,较之传统的做法,算法的复杂度降低。
(2)针对多幅图像到单幅图像的超分辨率重建问题,研究了种基于概率论与集合论相集成的MAP/POCS混合方法,推导了实现该算法的方程,并将单幅图像重建算法的剥离方法应用到算法的具体实现中。
(3)针对传统的基于插值的图像超分辨率重建方法,在讨论和分析其优点和不足之处后,提出了一种基于子像素位移B样条插值的图像超分辨率重建方法,该方法将原用于单幅图像到单幅图像超分辨率重建的B样条插值技术引入到多幅图像到单幅图像超分辨率重建中,利用相互间存在子像素位移的多幅图像上的附加信息来提高分辨率。
(4)针对超分辨率重建过程中的若干关键问题,进行了深入的探讨,内容包括降晰函数的辨识、巨型方程组的解法以及自由运动的超分辨率重建等许多问题,对于降晰函数的估计就信噪比的高低讨论了频域法和误差参数估计法,对于方程组的计算提出了一种近似算子的有效预处理方式。
(5)初步探讨了图像超分辨率重建的评价准则问题,提出了剖密度曲线CD图像超分辨率重建的评价准则。并就评价准则问题提出了一些想法,作为开问题出现在论文中。
Image super-resolution reconstruction is the image processing technology to produce the image of the high-quality, high-resolution from the low quality, low-resolution in the single or multi-images. In the thesis, it is elaborated and the algorithms involved are focused on. Briefly speaking, the main work includes one image reconstruction from one image and several images (or image sequence), image sequence reconstruction from image sequence, the criterion for super-resolution, etc.The research is listed as follows.
First, the research background and the situation at home and abroad of the art are reviewed, with its presence in various fields of military and civilian application indicated. Furthermore, an overview of current methods employed to the SR reconstruction is given, the fundamental skill, difficult issue and future development are all discussed. Based on these, the relation and the difference between the SR reconstruction and the technologies related are further such as image restoration, resolution, image enhancement and blur, etc. clarified.
For the problem of one image super resolution reconstruction from one image, a novel method is developed. A flaking method is suggested in the design of the algorithm; a more efficient approach is presented in the implement of the algorithm, the method avoids the operations of huge matrix. Compared with the traditional method, it is efficient and low complexity.
As for the problem of one image super resolution reconstruction from one image, we develop a novel method. A flaking method is suggested in the design of the algorithm; a more efficient approach is presented in the implement of the algorithm, our method runaround the operations of huge matrix. So, comparing our method with traditional method, the former is efficient and low complexity.
As far as super-resolution construction from image sequence to single image is concerned, a new B-spline interpolation method based on the image sequence is proposed by using the additional data in the sequence of existing mobile-related sub-pixel to improve the resolution. Besides, a integrated MAP/POCS hybrid approach is also proposed based on probability theory and the collection methods, with the derivation of the equations of the algorithm presented and spin-off of a single image reconstruction algorithm method applied to the specific algorithm implementation.
Some key problems including the model of image degradation, the estimation of blurring function and the method for big size equation system in super resolution reconstruction are studied deeply. For the high and low SNR, the frequency method and error-parameter estimative method are discussed; for the big size system, an effect pre-process method is considered.
In the last part of the thesis, some methods for the criterion of super-resolution are presented and the method of profile density curve is introduced. We also proposed some ideas as open problems for this problem.
引文
[1]Gonzalez R.C, Woods R.E.数字图像处理(第二版)(英文版)[M].北京：电了工业出版社,2002.
[2]章毓晋.图像工程(上册)(图像处理和分析第二版)[M].北京：清华大学出版社,2006.
[3]Mallats.著.陈刚,张宜,池哲儒译,应用数学和信号处理相遇[J].高校应用数学学报,1999,14(3)：348-366.
[4]肖亮.基于变分PDE和多重分形的图像建模理论、算法与应用[D].南京：南京理工大学,2003.
[5]Zhang Jian, Fan Xiaoping, Huang Cailun, Yu Guohua, A New Method of Image Restoration Based on Least Squares[J], Journal of Information and Computational Science,2008,5 (2):837-844.
[6]V.Patanavijit, S.Jitapunkul, A Robust Iterative Multiframe Super-resolution Reconstruction Using a Bayesian Apporach with Lorentzian Norm[A]. The 10th IEEE singapore International Conference on Communication Systems[C]. 255-259,2006.
[7]S.Battiato, G.Gallo, M.Mancuso, G.Messina, F.Stanco, Analysis and characterization of super-resolution reconstruction methods[A]. Proceedings of SPIE[C] 5017:323-331,2003.
[8]Protter, M. Elad, M. Takeda, H. Milanfar, P. Generalizing the Nonlocal-Means to Super-Resolution.IEEE Transactions on Image Processing, 2009,18(1):36-51.
[9]Wen-Ze Shao, Zhi-Hui Wei.Edge-and-corner preserving regularization for image interpolation and reconstruction[J], Image and Vision Computing, 2008(26)12:1591-1606.
[10]Yang, H. Gao, J. Wu, Z. Blur Identification and Image Super-Resolution Reconstruction Using an Approach Similar to Variable Projection[J]. IEEE signal processing letters.2008,15:289-292.
[11]Guilherme Holsbach Costa, Jose Carlos, Moreira Bermudez. Statistical Analysis of the LMS Algorithm Applied to Super-Resolution Image Reconstruction[J]. IEEE Transactions on Signal Processing.2007,55(5):2084-2095.
[12]Wang, C. Xue, P. Lin, W. Improved Super-Resolution Reconstruction From Video[J]. IEEE Transactions on Circuits and Systems for Video Technology. 2006,16:1411-1422.
[13]Ben-Ezra, M. Zomet, A. Nayar, S.K. Video super-resolution using controlled subpixel detector shifts[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence.2005,27(6):977-987.
[14]Akgun, T. Altunbasak, Y. Mersereau, R.M. Super-resolution reconstruction of hyperspectral images[J]. IEEE Transactions on Image Processing.2005, 14(11):1860-1875.
[15]Gunturk, B.K. Gevrekci, M. High-resolution image reconstruction from multiple differently exposed images[J]. IEEE signal processing letters.2006, 13(4):197-200.
[16]Marcelo V. W. Zibetti Joceli Mayer. Fermin S. V. Bazan. Determining the parameters in regularized super-resolution reconstruction [A]. IEEE International Conference on Acoustics, Speech and Signal Processing[C],2008,853-856.
[17]T.Komatsu, K.Aizawa, T.Igarashi, T.Saito. Signal-processing based method for acquiring very high resolution image with multiple cameras and its theoretical analysis[A].Proc.Inst.Elec[C].Eng., Feb.1993,140,(1):19-25.
[18]S.Chaudhuri, Ed., Super-Resolution Imaging.Norwell[M], MA:Kluwer,2001.
[19]R.Y.Tsai, T.S.Huang.Multipleframe image restoration and registration[A].In Advances in Computer Vision and Image Processing[C].Greenwich, CT:JAI Press Inc.,1984.317-339.
[20]T.Komatsu, T.Igarashi, K.Aizawa, T.Saito.Very high resolution imaging scheme with multiple different-aperture cameras[A]. Signal Processing.Image Communication[A], Dec.1993,:511-526.
[21]S.P.Kim, N.K.Bose, H.M.Valenzuela.Recursive reconstruction of high resolution image from noisy undersampled multiframes[J].IEEE Transactions on Acoustics, Speech, Signal Processing.1990,38:1013-1027.
[22]S.P.Kim, W.Y.Su.Recursive high-resolution reconstruction of blurred multiframe images. IEEE Transactions on Image Processing[J], Oct.1993,2:534-539.
[23]N.R.Shah, A.Zakhor.Resolution enhancement of color video sequences[J].IEEE Transactions on Image Processing,1999,8:879-885.
[24]H.C.Andrews, B.R.Hunt, Digital Image Restoration.Englewood Cliffs[M], NJ: Prentice-Hall,1977.
[25]A.K.Katsaggelos, Ed.DigitalImage Restoration. Heidelberg, Germany[A]. Springer-Verlag. Springer. vol.23,1991.
[26]I.J.Schoenberg.Cardinal interpolation and spline functions [J]. J.Approx. Theory.,1969,2:167-206.
[27]R.E.Crochiere, L.R.Rabiner.Interpolation and decimation of digital signals-A turorial review[J].Proc.IEEE, Mar.1981,69(3):300-331.
[28]M.Unser, A.Aldroubi, M.Eden.Enlargement or reduction of digital images with minimum loss of information[J].IEEE Transactions on Image Processing,.1995, 4(3):247-258.
[29]J.L.Harris.Diffraction and resolving power[J]. J.Opt.Soc.Am., July 1964, 54:931-936.
[30]Wirawan, P.Duhamel, H.Maitre.Multi-channel high resolution blind image restoration[A].Proc.IEEE ICASSP[C], AZ, Nov.1989.3229-3232.
[31]Besag J.E. Spatialinieraction and the statistiealan alysis of lattieesy stems(with discussion) [J]. J.Roy.Statist. Soc,1974,36(2):192-36.
[32]R.W.Gerchberg.Super-resolution through error energy reduction[J].Optica Acta, 1974,211(9):709-720.
[33]G.Toraldo di Francia.Resolving power and information[J].J.Opt.Soc.Am., July 1955,5:497-501.
[34]H.Ur, D.Gross.Improved resolution from subpixel shifted pictures[J]. CVGIP: Graph. Models Image Processing,1992,54(2):181-186.
[35]E.Kaltenbacher, R.C.Hardie.High-resolution infrared image reconstruction using multiple low-resolution aliased frames[A].Proc IEEE Nat.Aerospace Electronics Conf. Dayton[C], OH.1996,702-709.
[36]刘淼,曹汉强,李旭涛,王勃飞,基于运动估计误差和边缘约束的超分辨率重构[J],中国图象图形学报,2007,12(7)：1168-1172.
[37]B.C.Tom, A.K.Katsaggelos.Resolution enhancement of video sequences using motion compensation[A]. Proc IEEE Int Conf Image Processing. Lausanne, Switzerland[C].1996,1:713-716.
[38]B.C.Tom, A.K.Katsaggelos.Resolution enhancement of color video[A].Proc Conf Eur Signal Processing[C].1996.1:145-148.
[39]M.K.Ozkan, A.M.Tekalp, M.I.Sezan.POCS-based restoration of space-varying blurred images[J]. IEEE Transactions on Image Processing,1994,3(4):450-454.
[40]J.Patti, M.Sezan, A.M.Tekalp.High-resolution image reconstruction from a low-resolution image sequence in the presence of time-varying motion blur[A].Proc IEEE Int Conf Image Processing.Austin[C], TX.1994.343-347.
[41]J.Patti, M, I.Sezan, A.M.Tekalp.High-resolution standards conversion of low resolution video[A].In:Proc IEEE Int Conf ASSP.Detroit[C], MI.1995.2197-2200.
[42]J.Patti, M.I.Sezan, A.M.Tekalp.Robust methods for high-quality stills from interlaced video in the presence of dominant motion[J].IEEE Transactions on Circuits and Systems for Video Technology,1997,7(2):328-342.
[43]Tokiu, A.T.Erdem, M.I.Sezan, A.M.Tekalp.Tracking motion and intensity variations using hierarchical 2-D mesh modeling for synthetic object transfiguration[J].Graphical Models and Image Processing.1996,58(6):553-573.
[44]周亮,朱秀昌,基于Bayesian理论的压缩视频超分辨率重构算法,中国图象图形学报[J],2006,11(5)：730-735.
[45]R.R.Schultz, R.L.Stevenson.A Bayesian approach to image expansion for improved definition[J]. IEEE Transactions on Image Processing.1994, 3:233-242.
[46]邵文泽,韦志辉,基于广义Huber-MRF图像建模的超分辨率复原算法,软件学报[J],2007,18(5)：2434-2444.
[47]田岩,王志成, 柳健,图像序列的快速超分辨率恢复算法[J],电子学报,2004,32(12)：2074-2077.
[48]M.Elad, A.Feuer.Super-resolution restoration of continuous image sequence using the LMS algorithm[A].In:Proc 18th IEEE Conf Israel[C], Tel-Aviv.1995, 2.2.5:1-5.
[49]M.Elad, A.Feuer.Super-resolution reconstruction of continuous image sequences[J].Proc Int Conf Image Processing-ICIP1999[C].Kobe, Japan.1999.459-463.
[50]S.Baker, T.Kanade.Limits on super-resolution and how to break them.In:Proc[A].IEEE Int Conf Computer Vision and Pattern Recognition[C].2000.372-279.
[51]G.Sheppard, K.Panchapakesan, A.Bilgin, B.R.Hunt, M.W.Marcellin.Lapped nonlinear interpolative vector quantization and image super-resolution[J].IEEE Transactions on Image Processing.2000,9(2):295-298.
[52]Y.Altunbasak, A.J.Patti.A fast method of reconstructing high-resolution panoramic stills from MPEG-compressed video[A].Conf Multimedia Signal Processing.Los Angeles[C], CA.1998.7-9.
[53]K.Jensen, D.Anastassiou.Spatial resolution enhancement of images using nonlinear interpolation[A]. Proc IEEE ICASSP90[C].1990.2045-2048.
[54]Goodman J.W.Introduction to Fourier Optics[M]. NewYork:MeGrow Hill,1968.
[55]HarrisJ.L.Diffaction and Resolving Power. J.O.S.A.,1964,54(7):931-936.
[56]李衍达.信号重构理论及其应用[N].北京：清华大学出版社,1991.
[57]AndrewsH.C., HuntB.R.DigitalImageRestoration[M]. Englewood Cliffs, NJ:Prentiee Hall,1977.
[58]Tekalp A.M., OzkanM.K., Sezan M.I. High-resolution image reconstruction from lower-esolution image sequences and space-varying image estoration[A]. Proceedings of the IEEE Int.Conf. on Aeousties, Speech and Signal Processing[C], San Franeiseo, CA,1992,3:169-172.
[59]Kaltenbacher E., Hardie R.C. High-resolution infrared image reconstruction using multiple low resolution aliiased frames[A]. In:Proceedings of the IEEE National Aerospace Electronics Conference (NAECON) [C], Dayton, OH,1996, 2:702-709.
[60]Kim S.P., Bose N.K., Valenzuela H.M. Recursive reconstruction of high resolution image from noisy under-sampled multi-frames[J]. IEEE Transactions on Acousties, Speech and Signal Processing,1990,38(6):1013-1027.
[61]Kim S.P., Su W.Y. Recursive high-resolution reconstruction of blured multi-frame images[A]. Proceeding of the IEEE Int.Conf.on Aeousties Speech and Signal Processing[C], Toronto, Canada,1991,4:2977-2980.
[62]Kim S.P., SuW.Y. Recursive high-resolution reconstruction of blurred multi-frame images[J]. IEEE Transactions on Image Processing,1993, 2(4):534-539.
[63]Bose N.K., KimH.C., ValenzuelaH.M. Recursive total least Squares algorithm for image reconstruction from noisy, under-sampled multi-frames[J]. Multidimensional Systems and Signal Processing,1993,4(3):253-268.
[64]Davila C.E. Efficient reeursive total least squares algorithms for FIR adaptive filtering[J]. IEEE Transactions on Signal Processing,1994,42(2):268-280.
[65]Bose N.K., Kim H.C., Zhou B. Performance analysis of the TLS algorithm for image reconstruction from a sequence of under-sampled noisy and blurred frames [A]. Proceedings of the IEEE International Conference on Image Processing[C], Austin, TX,1994,3:571-575.
[66]Kim H.C. High resolution image reconstruction from under-sampled multi-frames[D]. Pennsylvania:Pennsylvania State University,1994.
[67]Elad M., FeuerA. Restoration of a single super-resolution image from several blurred, noisy, and under-sampled measured images[J]. IEEE Transactions on Image Processing,1997,6(12):1646-1658.
[68]RajanD., Chaudhuri S. Generation of super-resolution images form blurred observations using an MRF medel[J]. Jounal of Mathematical Imaging and Vision,2002,16(1):5-15.
[69]RajanD., ChaudhuriS. Simultaneous estimation of super-resolved intensity and depth maps from low resolution defocused observations of a scene[A]. Proc.IEEEint.Conf.ComPuter Vision[C], Vaneouver, Canada 2001,113-118.
[70]JoshiM.V., ChaudhuriS.Super-resolution imaging:use of zoom as a cue[A]. Proc.Indian Conf. Vision, Graphics and Image Processing, Anmedabad[C], India.2002,439-444.
[71]Inria Rennes, Bretagne Atlantique, Photometry-based visual servoing using light reflexion models[A], Proceedings of the IEEE international conference on Robotics and Automation[C],2009,464-469.
[72]JoshiM.V, ChaudhuriS., Panuganti R. Super-resolution imaging:use of zoom as a cue[J]. Image and Vision Computing,2004,22(14):1185-1196.
[73]Rajan D., Chaudhuri S. Generalized intepolation and its applications in super-resolution imaging[J]. Image and Vision ComPuting,2001, 19(13):957-969.
[74]曹聚亮.图像超分辨率处理、成像及其相关技术研究[D].长沙：国防科技大学,2004.
[75]袁小华.超分辨率图像恢复中的方法研究[D].南京：南京理工大学,2005.
[76]BakerS., KanadeT.Hallueinating faces[D]. Camegie Mellon University,1999.
[77]BakerS., KanadeT. Limits on super-resolution and how to break them[A]. Proceeding of IEEE Cont. on Computer Vision and Patten Recognition[C], 2000,2:372-379.
[78]BakerS., KanadeT.Limits on super-resolution and how to break them[J]. IEEE Transactions on PAMI,2002,24(9):1167-1183.
[79]BakerS., KanadeT. Super-resolution:reconstruction or reeognition? [M]. IEEE EURASIP Workshop on Nonlinear Signal and Image Processing, Baltimore, Maryland,2001.
[80]GuntorkB.K., Bator A.U., AltUnbasak Y,Ill HayesM.H., Mersereau, R.M. Eigenface-domain super-resolution for face recognition[J]. IEEE Transactions on Image processing,2003,12(5):597-606.
[81]Freeman W.T., PasztorE.C., Exampled-based super-resolution[J]. IEEE Computer Graphies and Applications,2002,22(2):56-65.
[82]M.Irani, S.Peleg.Improving resolution by image registration.CVGIP[J].Graphical Models and Image Proc.,1991,53:231-239.
[83]S.Mann, R.W.Picard.Virtual bellows:Constructing high quality stills from video[A]. Proc. IEEE Int.Conf. Image Processing[C], Austin, TX, Nov.1994.363-367.
[84]A.M.Tekalp, M.K.Ozkan, M.I.Sezan.High-resolution image reconstruction from lower-resolution image sequences and space varying image restoration[A]..IEEE Int. Conf.Acoustics, Speech and Signal Processing(ICASSP) [C], San Francisco, CA., Mar.1992,3:169-172.
[85]B.C.Tom, A.K.Katsaggelos.Resolution enhancement of video sequences using motion compensation[A]. IEEE Int Conf Image Processing. Lausanne, Switzerland[C].1996,1:713-716.
[86]B.C.Tom, A.K.Katsaggelos.Resolution enhancement of monochrome and color video using motion compensation[J]. IEEE Transactions on Image Processing, 2001,10(2):278-287.
[87]B.C.Tom, A.K.Katsaggelos.Resolution enhancement of color video[A]. Proc Conf Eur Signal Processing[C].1996.1:145-148.
[88]H.Ur, D.Gross.Improved resolution from sub-pixel shifted pictures[J].CVGIP:Graphical Models and image Processing,1992,54:181-186.
[89]J.L.Brown. Multi-channel sampling of low pass signals[J]. IEEE Transactions on Circuits Syst.,1981,28:101-106.
[90]Papoulis. Generalized sampling theorem[J]. IEEE Transactions on Circuits Syst.1977,24:652-654.
[91]M.S.Alam, J.GBognar, R.C.Hardie, B.J.Yasuda.Infrared image registration and high-resolution reconstruction using multiple translationally shifted aliased video frames[J]. IEEE Transactions on Instrum.Meas.,.2000,49:915-923.
[92]T.Komatsu, K.Aizawa, T.Igarashi, T.Saito.Signal-processing based method for acquiring very high resolution image with multiple cameras and its theoretical analysis[J]. Proc.Inst.Elec. Eng.,1993,140, (1):19-25.
[93]H.J.Trussell, M.R.Civanlar.The landweber iteration and projection onto convex sets[J]. IEEE Transactions on Acoustics, Speech, and Signal Processing,1985, 33(6):1632-1633.
[94]L.Landweber.An iteration formula for Fredholm integral equations of the first kind[J]. Amer.J. Math.1951,73:615-624.
[95]T.Komatsu, T.Igarashi, K.Aizawa, T.Saito.Very high resolution imaging scheme with multiple different-aperture cameras[J]. Signal Processing:Image Communication, Dec.1993,5:511-526.
[96]N.R.Shah, A.Zakhor.Resolution enhancement of color video sequences[J]. IEEE Transactions on Image Processing,1999,8:879-885.
[97]David T.Sandwell.Biharnionic spline interpolation of Geo-3 and Seasat altimeter data[J]. Geophysical Research Letters.1987,14(2):139-142.
[98]Richard Franke. Smooth interpolation of scattered data by local thin plate splines[J]. Comput. Math.Appl.1982,8(4):273-281.
[99]N.Nguyen, P.Milanfar. An efficient wavelet-based algorithm for image superresolution[A]. Proc.Int.Conf.Image processing[C],2000,2:351-354.
[100]TakedaH., Farsiu5., Milanfar P. Kenel regression for image Processing and reconstruction[J]. IEEE Trans. Image Processing,2007,16(2):349-366.
[101]HuniB.R., Sementilli P.J. Description of a Poisson imagery super-resolution algorithm. Astronomical Data Analysis Software and System,1992, 25:196-199.
[102]Sementilli P.J., Nadar M.S., Hunt B.R. Poisson MAP super-resolution estimator with smoothness onstraint[A]. Proceedings of SPIE Neural and Stochastie Metheds in Image and Signal Processing II[C],1993,2032:2-13.
[103]Cheeseman P., Kanefsky B., Kraft R., Stutz J., Hanson R. Super-resolved surface reconstruction from multiple images [A]. NASA Ames Research Centor, Moffett Field, CA, Tech.ReP[C].FIA-94-12,1994.
[104]Sehultz RR, Stevenson RL. Extraction of high-resolution frames from video sequenees[J].IEEE Transactions on Image Processing,1996,5(6):996-1011.
[105]Sehultz RR, Stevenson RL. A Bayesian approach to image expansion for improve definition[J]. IEEE Transactions on Image Processing,1994, 3(3):233-242.
[106]Elad M., Feuer A.Restoration of a single super-resolution image from several bluured, noisy, and under-sampled measured mages[J].IEEE Transactions on Image Processing,1997,6(12):1646-1658.
[107]Hardie R.C., Tuinstra T.R., Bognar J., Bamard K.J., Armstrong E. High resolution image reconstruction from digital video with global and non-global scene motion[A]. Proceedings of the IEEE International Conference on Image Processing[C], Santa Barbara, CA,1997,1:153-156.
[108]Hong M.C., KangM.G., Katsaggelos A.K. A regularized multi-channel restoration apppoach for globally optimal high resolution video sequence[A]. SPIE VCIP[C], San Jose, CA,1997,3024:1306-1317.
[109]Hong M.C., KangM.G., Katsaggelos A.K. An iterative weighted regularized algorithm for improving the resolution of video sequences[A]. In:Proc.Int.Conf. ImageProcessing[C],1997,2:474-477.
[110]Hardie R.C., Bamard K.J., Bognar J.G., Armstrong E.E., Watson E.A. High resolution image reconstruction from sequence of rotated and translated frames and its application to an infrared imaging system[J]. Optical Engineering,1998, 73(1):247-260.
[111]Nguyen N.X. Numerical algorithms for image super-resolution[D]. Califomia:Stanford University,2000.
[112]Nguyen N., Milanfar P., Golub G. Efficient generalized cross-validation with applications to parametric image restoration and resolution enhancement[J]. IEEE Trans. Image Processing,2001,10(9):1299-1308.
[113]Elad M. On the bilateral filter and ways to improve it[J]. IEEE Trans.on Image Processing,2002,11(10):1141-1151.
[114]Farsiu S., Robinson D., Elad M., Milanfar P. Fast and robust multi-frame super-resolution[J]. IEEE Transactions on Image Processing,2004, 13(10):1327-1344.
[115]Capel D., Zisserman A. Super-resolution enhancement of text image sequences[A]. Proc. Intl.Con. Patt.Recog[C],2000,1:600-605.
[116]Kim H., HongK.S. Variational approaches to super-resolution with contrast enhancement and anisotropic diffusion[J]. Journal of Electronic Imaging,2003, 12(2):244-251.
[117]Ng M.K., ShenH.F., lam E.Y, zhangL.P. A total variation regularization based super-resolution reconstruction algorithm for digital video[J]. EURASIPJoumal on Applied signal Processing,2007,7(2):114-129.
[118]M.K.Ozkan, A.M.Tekalp, M.I.Sezan.POCS-based restoration of space-varying blurred images[J].IEEE Transactions on Image Processing,1994,3(4):450-454
[119]StarkH., Oskoui P. High resolution image recovery from image-plane arrays, using conv projeetions[J].J.Opt.Soc.Am.A,1989,6(11):1715-1726.
[120]Youla D.C.Image restoration by the method of convex projections:part 1 theory[J]. IEEE Transactions on Medical Imaging,1982,10(2):81-94.
[121]A.J.Patti, M.I.Sezan, A.M.Tekalp.Superresolution video reconstruction with arbitrary sampling lattices and nonzero aperture time[J].IEEE Transactions on Image Processing,1997,6(8):1064-1076.
[122]Tekalp A.M., Ozkan M.K., Sezan M.I. High-resolution image reconstruction from lower-resolution image sequences and space varying image restoration[A]. Proc.IEEE Int. Conf Aeousties, Speech and Signal Processing(ICASSP)[C], SanFraneisco, CA.,1992,169-172.
[123]J.Patti, M.I.Sezan, A.M.Tekalp.Robust methods for high-quality stills from interlaced video in the presence of dominant motion[J].IEEE Transactions on Circuits and Systems for Video Technology,1997,7(2):328-342.
[124]P.E.Eren, M.I.Sezan, A.M.Tekalp.Robust, object-based high-resolution image reconstruction from low-resolution video[J].IEEE Transactions on Image Processing,1997,6(10):1446-1451.
[125]Tokiu, A.T.Erdem, M.I.Sezan, A.M.Tekalp.Tracking motion and intensity variations using hierarchical 2-D mesh modeling for synthetic object transfiguration[J].Graphical Models and Image Processing.1996,58(6):553-573.
[126]B.C.Tom, A.K.Katsaggelos An iterative algorithm for improving the resolution of video sequences[A]. Proc.1996 SPIE Conf. Visual Communications and Image Processing[C], Orlando, FL, Mar.996.1430-1438.
[127]A.J.Patti, Y.Altunbasak.Artifact reduction for set theoretic super resolution image reconstruction with edge adaptive constraints and higher-order interpolants.IEEE[J].Transactions on Image Processing,2001,10(1):179-186
[128]Mallats.著.信号处理的小波导引(第2版)[M].杨力华,戴道清,黄文良,湛秋辉译.北京：机械工业出版社,2002.
[129]Li J., Sheng Y.L. Wavelet domain super-resolution reconstru ctionofinfrared image sequences[A]. Proceedings of SPIE[C],2001,4385:108-116.
[130]NgUyen N., Milanfar P. A wavelet-based interpolation-restoration method for super-resolution[J]. Circuits systems Signal Process,2000,19(4):321-338.
[131]Fadili M.J., StarekJ.L., Murtagh F. Inpainting and zooming using sparse representations[J]. The Computer Journal,2009,52(1):64-79.
[132]Jiji C.V., Chaudhuri S. Single-frame image super-resolution through contourlet learning[J]. EURASIP Journal on Applied signal Processing,2006,1:1-11.
[133]张地,杜明辉.超分辨率图像重建边缘振荡的高效去除算法[J].信息与电子工程,2004,4(4)：81-85.
[134]相里斌,李英才,刘良云.超分辨率图像重构技术的仿真实验研究[J].中国图象图形学报,2001,6(7)：629-635.
[135]王程,王润生.基于MAP框架的图像序列超分辨率和模板匹配[J].计算机学报,2003,26(8)：961-967.
[136]邵凌,丁佩律,张立明,胡波.从多帧低分辨率图像序列中获取高分辨率图像的算法研究[J].电子学报,2002,30(1)：58-61.
[137]邵凌,丁佩律,张立明,胡波.重建高分辨率图像的实时串行迭代算法[J].红外与毫米波学报,2002,21(2)：104-108.
[138]苏秉华,金伟其,牛丽红,刘广荣,刘明奇.基于Markov约束的泊松最大后验概率超分辨率图像复原法[J].光子学报,2002,31(4)：492-496.
[139]洪功义,姜显明.基于图像配准的POCS超分辨率图像重建[J].计算机仿真,2004,21(6)：145-147.
[140]黄丽,庄越挺,苏从勇,吴飞.基于多尺度和多方向特征的人脸超分辨率算法[J].计算机辅助设计与图形学学报,2004,16(7)：953-961.
[141]赵书斌,彭思龙.基于小波域HMT模型的图像超分辨率重建[J].计算机辅助设计与图形学学报,2003,15(11)：1347-1352.
[142]张新明,沈兰荪.在小波变换域内实现图像的超分辨率复原[J].计算机学报,2003,26(9)：1183-1189.
[143]Jiang Z.D., Lin H., Bao H.J., Ma L.Z. A super-resolution methed with EWA[J]. Journal of Computer Science and Technology,2003,18(6):822-832.
[144]汪雪林,文伟,彭思龙.基于小波域局部高斯模型的图像超分辨率[J].中国图象图形学报,2005,28(6)：1006-1012.
[145]程燕.图像超分辨率重建关键技术的研究[D].上海：上海交通大学,2007.
[146]潘逢治,张立明.用神经网络恢复残差的图像超分辨率算法[J].电子学报,2004,32(1)：161-165.
[147]韩玉兵.图像及视频序列的超分辨率重建[D].南京：东南大学,2005.
[148]郭晓新.超分辨率重建问题的研究[D].吉林：吉林大学,2005.
[149]教育部科技发展中心.哈工大开创性成果让卫星图像更清晰.http://www.cutech.edu.cn/cn/zggx/zxzx/2006/09/1179971253618210.htm.
[150]ZhangJian, Fan Xiaoping, Huang Cailun, A Method of Super-Resolution
Image Restoration Based on Separation[A], Proceedings of the 26th Chinese Control Conference[C],2007,275-277.
[151]张剑,田岩,柳健.一种基于分离思想的超分辨率复原方法[J].华中科技大学学报(自然科学版)2003,31(8)：27-28,31.
[152]Michael Elad, Yacov Hel-or, A Fast Super-resolution Reconstruction Algorithm for Pure Translational Motion and Common Space-invariant Blur[J]. IEEE Transactions on Image Processing,2001,10(8):1187-1193.
[153]Yubing Han, Feng Shu, Qingchuan Zhang, Image super-resolution reconstruction based on adaptive interpolation norm regularization[J]. Intelligent Signal Processing and Communication Systems, P.698-701,2007.
[154]ZhangJian, Fan Xiaoping, Huang Cailun, Tian Yuan, Multi-spectral Image Super-Resolution Reconstruction Based on B-spline Interpolation[A], SPIE Sixth International Symposium on Multispectral Image Processing and Pattern Recognition[C].2009,7494:165-171.
[155]刘洪臣,杨旭强,冯勇, 亚像元成像系统B样条插值方法[J].光电工程.2006,33(2)：90-94.
[156]Farsiu S, Elad M, Milanfar P. Multiframe demosaicing and super-resolution of color images[J].IEEE Transaction on Image Processing,2006,15 (1):141-160.
[157]A. M. Tekalp, M. K. Ozkan, and M. I. Sezan. High-resolution image reconstruction from lower-resolution image sequences and space-varying image restoration[A]. ICASSP 1992 [C], San Francisco, vol. Ⅲ:169-172.
[158]A.J.Patti. M.I.Sezan, and A.M.Tekalp, High-resolution standards conversion of low-resolution video[A], Proc. IEEE. Int. conf. Acoustics, Speech and Signal Processing (ICASSP)[C],1995, Vol.Ⅱ:2197-2200.
[159]R. R. Schultz and R. L. Stevenson, Improved definition video frame enhancement[A], IEEE Int. Conf. Acoustics, Speech, and Singal Processing (ICASSP)[C],1995, Vol.Ⅳ:2169-2172.
[160]邹谋炎,反卷积和信号复原[M],北京,国防工业出版社,2001.
[161]Zhang Jian, Fan Xiaoping, Huang Cailun, On Evaluation Criterion of Image Super-Resolution Reconstruction[A], Proceedings of IEEE ICICIC07[C],2007, 177-182.
[162]A.K Katsaggelos and S.N. Efstratiadis, A class of iterative signal restoration algorithm[J].IEEE Trans. Acoust.,Speech,Signal Processing,2000, Vol.38:778-786
[2]章毓晋.图像工程(上册)(图像处理和分析第二版)[M].北京：清华大学出版社,2006.
[3]Mallats.著.陈刚,张宜,池哲儒译,应用数学和信号处理相遇[J].高校应用数学学报,1999,14(3)：348-366.
[4]肖亮.基于变分PDE和多重分形的图像建模理论、算法与应用[D].南京：南京理工大学,2003.
[5]Zhang Jian, Fan Xiaoping, Huang Cailun, Yu Guohua, A New Method of Image Restoration Based on Least Squares[J], Journal of Information and Computational Science,2008,5 (2):837-844.
[6]V.Patanavijit, S.Jitapunkul, A Robust Iterative Multiframe Super-resolution Reconstruction Using a Bayesian Apporach with Lorentzian Norm[A]. The 10th IEEE singapore International Conference on Communication Systems[C]. 255-259,2006.
[7]S.Battiato, G.Gallo, M.Mancuso, G.Messina, F.Stanco, Analysis and characterization of super-resolution reconstruction methods[A]. Proceedings of SPIE[C] 5017:323-331,2003.
[8]Protter, M. Elad, M. Takeda, H. Milanfar, P. Generalizing the Nonlocal-Means to Super-Resolution.IEEE Transactions on Image Processing, 2009,18(1):36-51.
[9]Wen-Ze Shao, Zhi-Hui Wei.Edge-and-corner preserving regularization for image interpolation and reconstruction[J], Image and Vision Computing, 2008(26)12:1591-1606.
[10]Yang, H. Gao, J. Wu, Z. Blur Identification and Image Super-Resolution Reconstruction Using an Approach Similar to Variable Projection[J]. IEEE signal processing letters.2008,15:289-292.
[11]Guilherme Holsbach Costa, Jose Carlos, Moreira Bermudez. Statistical Analysis of the LMS Algorithm Applied to Super-Resolution Image Reconstruction[J]. IEEE Transactions on Signal Processing.2007,55(5):2084-2095.
[12]Wang, C. Xue, P. Lin, W. Improved Super-Resolution Reconstruction From Video[J]. IEEE Transactions on Circuits and Systems for Video Technology. 2006,16:1411-1422.
[13]Ben-Ezra, M. Zomet, A. Nayar, S.K. Video super-resolution using controlled subpixel detector shifts[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence.2005,27(6):977-987.
[14]Akgun, T. Altunbasak, Y. Mersereau, R.M. Super-resolution reconstruction of hyperspectral images[J]. IEEE Transactions on Image Processing.2005, 14(11):1860-1875.
[15]Gunturk, B.K. Gevrekci, M. High-resolution image reconstruction from multiple differently exposed images[J]. IEEE signal processing letters.2006, 13(4):197-200.
[16]Marcelo V. W. Zibetti Joceli Mayer. Fermin S. V. Bazan. Determining the parameters in regularized super-resolution reconstruction [A]. IEEE International Conference on Acoustics, Speech and Signal Processing[C],2008,853-856.
[17]T.Komatsu, K.Aizawa, T.Igarashi, T.Saito. Signal-processing based method for acquiring very high resolution image with multiple cameras and its theoretical analysis[A].Proc.Inst.Elec[C].Eng., Feb.1993,140,(1):19-25.
[18]S.Chaudhuri, Ed., Super-Resolution Imaging.Norwell[M], MA:Kluwer,2001.
[19]R.Y.Tsai, T.S.Huang.Multipleframe image restoration and registration[A].In Advances in Computer Vision and Image Processing[C].Greenwich, CT:JAI Press Inc.,1984.317-339.
[20]T.Komatsu, T.Igarashi, K.Aizawa, T.Saito.Very high resolution imaging scheme with multiple different-aperture cameras[A]. Signal Processing.Image Communication[A], Dec.1993,:511-526.
[21]S.P.Kim, N.K.Bose, H.M.Valenzuela.Recursive reconstruction of high resolution image from noisy undersampled multiframes[J].IEEE Transactions on Acoustics, Speech, Signal Processing.1990,38:1013-1027.
[22]S.P.Kim, W.Y.Su.Recursive high-resolution reconstruction of blurred multiframe images. IEEE Transactions on Image Processing[J], Oct.1993,2:534-539.
[23]N.R.Shah, A.Zakhor.Resolution enhancement of color video sequences[J].IEEE Transactions on Image Processing,1999,8:879-885.
[24]H.C.Andrews, B.R.Hunt, Digital Image Restoration.Englewood Cliffs[M], NJ: Prentice-Hall,1977.
[25]A.K.Katsaggelos, Ed.DigitalImage Restoration. Heidelberg, Germany[A]. Springer-Verlag. Springer. vol.23,1991.
[26]I.J.Schoenberg.Cardinal interpolation and spline functions [J]. J.Approx. Theory.,1969,2:167-206.
[27]R.E.Crochiere, L.R.Rabiner.Interpolation and decimation of digital signals-A turorial review[J].Proc.IEEE, Mar.1981,69(3):300-331.
[28]M.Unser, A.Aldroubi, M.Eden.Enlargement or reduction of digital images with minimum loss of information[J].IEEE Transactions on Image Processing,.1995, 4(3):247-258.
[29]J.L.Harris.Diffraction and resolving power[J]. J.Opt.Soc.Am., July 1964, 54:931-936.
[30]Wirawan, P.Duhamel, H.Maitre.Multi-channel high resolution blind image restoration[A].Proc.IEEE ICASSP[C], AZ, Nov.1989.3229-3232.
[31]Besag J.E. Spatialinieraction and the statistiealan alysis of lattieesy stems(with discussion) [J]. J.Roy.Statist. Soc,1974,36(2):192-36.
[32]R.W.Gerchberg.Super-resolution through error energy reduction[J].Optica Acta, 1974,211(9):709-720.
[33]G.Toraldo di Francia.Resolving power and information[J].J.Opt.Soc.Am., July 1955,5:497-501.
[34]H.Ur, D.Gross.Improved resolution from subpixel shifted pictures[J]. CVGIP: Graph. Models Image Processing,1992,54(2):181-186.
[35]E.Kaltenbacher, R.C.Hardie.High-resolution infrared image reconstruction using multiple low-resolution aliased frames[A].Proc IEEE Nat.Aerospace Electronics Conf. Dayton[C], OH.1996,702-709.
[36]刘淼,曹汉强,李旭涛,王勃飞,基于运动估计误差和边缘约束的超分辨率重构[J],中国图象图形学报,2007,12(7)：1168-1172.
[37]B.C.Tom, A.K.Katsaggelos.Resolution enhancement of video sequences using motion compensation[A]. Proc IEEE Int Conf Image Processing. Lausanne, Switzerland[C].1996,1:713-716.
[38]B.C.Tom, A.K.Katsaggelos.Resolution enhancement of color video[A].Proc Conf Eur Signal Processing[C].1996.1:145-148.
[39]M.K.Ozkan, A.M.Tekalp, M.I.Sezan.POCS-based restoration of space-varying blurred images[J]. IEEE Transactions on Image Processing,1994,3(4):450-454.
[40]J.Patti, M.Sezan, A.M.Tekalp.High-resolution image reconstruction from a low-resolution image sequence in the presence of time-varying motion blur[A].Proc IEEE Int Conf Image Processing.Austin[C], TX.1994.343-347.
[41]J.Patti, M, I.Sezan, A.M.Tekalp.High-resolution standards conversion of low resolution video[A].In:Proc IEEE Int Conf ASSP.Detroit[C], MI.1995.2197-2200.
[42]J.Patti, M.I.Sezan, A.M.Tekalp.Robust methods for high-quality stills from interlaced video in the presence of dominant motion[J].IEEE Transactions on Circuits and Systems for Video Technology,1997,7(2):328-342.
[43]Tokiu, A.T.Erdem, M.I.Sezan, A.M.Tekalp.Tracking motion and intensity variations using hierarchical 2-D mesh modeling for synthetic object transfiguration[J].Graphical Models and Image Processing.1996,58(6):553-573.
[44]周亮,朱秀昌,基于Bayesian理论的压缩视频超分辨率重构算法,中国图象图形学报[J],2006,11(5)：730-735.
[45]R.R.Schultz, R.L.Stevenson.A Bayesian approach to image expansion for improved definition[J]. IEEE Transactions on Image Processing.1994, 3:233-242.
[46]邵文泽,韦志辉,基于广义Huber-MRF图像建模的超分辨率复原算法,软件学报[J],2007,18(5)：2434-2444.
[47]田岩,王志成, 柳健,图像序列的快速超分辨率恢复算法[J],电子学报,2004,32(12)：2074-2077.
[48]M.Elad, A.Feuer.Super-resolution restoration of continuous image sequence using the LMS algorithm[A].In:Proc 18th IEEE Conf Israel[C], Tel-Aviv.1995, 2.2.5:1-5.
[49]M.Elad, A.Feuer.Super-resolution reconstruction of continuous image sequences[J].Proc Int Conf Image Processing-ICIP1999[C].Kobe, Japan.1999.459-463.
[50]S.Baker, T.Kanade.Limits on super-resolution and how to break them.In:Proc[A].IEEE Int Conf Computer Vision and Pattern Recognition[C].2000.372-279.
[51]G.Sheppard, K.Panchapakesan, A.Bilgin, B.R.Hunt, M.W.Marcellin.Lapped nonlinear interpolative vector quantization and image super-resolution[J].IEEE Transactions on Image Processing.2000,9(2):295-298.
[52]Y.Altunbasak, A.J.Patti.A fast method of reconstructing high-resolution panoramic stills from MPEG-compressed video[A].Conf Multimedia Signal Processing.Los Angeles[C], CA.1998.7-9.
[53]K.Jensen, D.Anastassiou.Spatial resolution enhancement of images using nonlinear interpolation[A]. Proc IEEE ICASSP90[C].1990.2045-2048.
[54]Goodman J.W.Introduction to Fourier Optics[M]. NewYork:MeGrow Hill,1968.
[55]HarrisJ.L.Diffaction and Resolving Power. J.O.S.A.,1964,54(7):931-936.
[56]李衍达.信号重构理论及其应用[N].北京：清华大学出版社,1991.
[57]AndrewsH.C., HuntB.R.DigitalImageRestoration[M]. Englewood Cliffs, NJ:Prentiee Hall,1977.
[58]Tekalp A.M., OzkanM.K., Sezan M.I. High-resolution image reconstruction from lower-esolution image sequences and space-varying image estoration[A]. Proceedings of the IEEE Int.Conf. on Aeousties, Speech and Signal Processing[C], San Franeiseo, CA,1992,3:169-172.
[59]Kaltenbacher E., Hardie R.C. High-resolution infrared image reconstruction using multiple low resolution aliiased frames[A]. In:Proceedings of the IEEE National Aerospace Electronics Conference (NAECON) [C], Dayton, OH,1996, 2:702-709.
[60]Kim S.P., Bose N.K., Valenzuela H.M. Recursive reconstruction of high resolution image from noisy under-sampled multi-frames[J]. IEEE Transactions on Acousties, Speech and Signal Processing,1990,38(6):1013-1027.
[61]Kim S.P., Su W.Y. Recursive high-resolution reconstruction of blured multi-frame images[A]. Proceeding of the IEEE Int.Conf.on Aeousties Speech and Signal Processing[C], Toronto, Canada,1991,4:2977-2980.
[62]Kim S.P., SuW.Y. Recursive high-resolution reconstruction of blurred multi-frame images[J]. IEEE Transactions on Image Processing,1993, 2(4):534-539.
[63]Bose N.K., KimH.C., ValenzuelaH.M. Recursive total least Squares algorithm for image reconstruction from noisy, under-sampled multi-frames[J]. Multidimensional Systems and Signal Processing,1993,4(3):253-268.
[64]Davila C.E. Efficient reeursive total least squares algorithms for FIR adaptive filtering[J]. IEEE Transactions on Signal Processing,1994,42(2):268-280.
[65]Bose N.K., Kim H.C., Zhou B. Performance analysis of the TLS algorithm for image reconstruction from a sequence of under-sampled noisy and blurred frames [A]. Proceedings of the IEEE International Conference on Image Processing[C], Austin, TX,1994,3:571-575.
[66]Kim H.C. High resolution image reconstruction from under-sampled multi-frames[D]. Pennsylvania:Pennsylvania State University,1994.
[67]Elad M., FeuerA. Restoration of a single super-resolution image from several blurred, noisy, and under-sampled measured images[J]. IEEE Transactions on Image Processing,1997,6(12):1646-1658.
[68]RajanD., Chaudhuri S. Generation of super-resolution images form blurred observations using an MRF medel[J]. Jounal of Mathematical Imaging and Vision,2002,16(1):5-15.
[69]RajanD., ChaudhuriS. Simultaneous estimation of super-resolved intensity and depth maps from low resolution defocused observations of a scene[A]. Proc.IEEEint.Conf.ComPuter Vision[C], Vaneouver, Canada 2001,113-118.
[70]JoshiM.V., ChaudhuriS.Super-resolution imaging:use of zoom as a cue[A]. Proc.Indian Conf. Vision, Graphics and Image Processing, Anmedabad[C], India.2002,439-444.
[71]Inria Rennes, Bretagne Atlantique, Photometry-based visual servoing using light reflexion models[A], Proceedings of the IEEE international conference on Robotics and Automation[C],2009,464-469.
[72]JoshiM.V, ChaudhuriS., Panuganti R. Super-resolution imaging:use of zoom as a cue[J]. Image and Vision Computing,2004,22(14):1185-1196.
[73]Rajan D., Chaudhuri S. Generalized intepolation and its applications in super-resolution imaging[J]. Image and Vision ComPuting,2001, 19(13):957-969.
[74]曹聚亮.图像超分辨率处理、成像及其相关技术研究[D].长沙：国防科技大学,2004.
[75]袁小华.超分辨率图像恢复中的方法研究[D].南京：南京理工大学,2005.
[76]BakerS., KanadeT.Hallueinating faces[D]. Camegie Mellon University,1999.
[77]BakerS., KanadeT. Limits on super-resolution and how to break them[A]. Proceeding of IEEE Cont. on Computer Vision and Patten Recognition[C], 2000,2:372-379.
[78]BakerS., KanadeT.Limits on super-resolution and how to break them[J]. IEEE Transactions on PAMI,2002,24(9):1167-1183.
[79]BakerS., KanadeT. Super-resolution:reconstruction or reeognition? [M]. IEEE EURASIP Workshop on Nonlinear Signal and Image Processing, Baltimore, Maryland,2001.
[80]GuntorkB.K., Bator A.U., AltUnbasak Y,Ill HayesM.H., Mersereau, R.M. Eigenface-domain super-resolution for face recognition[J]. IEEE Transactions on Image processing,2003,12(5):597-606.
[81]Freeman W.T., PasztorE.C., Exampled-based super-resolution[J]. IEEE Computer Graphies and Applications,2002,22(2):56-65.
[82]M.Irani, S.Peleg.Improving resolution by image registration.CVGIP[J].Graphical Models and Image Proc.,1991,53:231-239.
[83]S.Mann, R.W.Picard.Virtual bellows:Constructing high quality stills from video[A]. Proc. IEEE Int.Conf. Image Processing[C], Austin, TX, Nov.1994.363-367.
[84]A.M.Tekalp, M.K.Ozkan, M.I.Sezan.High-resolution image reconstruction from lower-resolution image sequences and space varying image restoration[A]..IEEE Int. Conf.Acoustics, Speech and Signal Processing(ICASSP) [C], San Francisco, CA., Mar.1992,3:169-172.
[85]B.C.Tom, A.K.Katsaggelos.Resolution enhancement of video sequences using motion compensation[A]. IEEE Int Conf Image Processing. Lausanne, Switzerland[C].1996,1:713-716.
[86]B.C.Tom, A.K.Katsaggelos.Resolution enhancement of monochrome and color video using motion compensation[J]. IEEE Transactions on Image Processing, 2001,10(2):278-287.
[87]B.C.Tom, A.K.Katsaggelos.Resolution enhancement of color video[A]. Proc Conf Eur Signal Processing[C].1996.1:145-148.
[88]H.Ur, D.Gross.Improved resolution from sub-pixel shifted pictures[J].CVGIP:Graphical Models and image Processing,1992,54:181-186.
[89]J.L.Brown. Multi-channel sampling of low pass signals[J]. IEEE Transactions on Circuits Syst.,1981,28:101-106.
[90]Papoulis. Generalized sampling theorem[J]. IEEE Transactions on Circuits Syst.1977,24:652-654.
[91]M.S.Alam, J.GBognar, R.C.Hardie, B.J.Yasuda.Infrared image registration and high-resolution reconstruction using multiple translationally shifted aliased video frames[J]. IEEE Transactions on Instrum.Meas.,.2000,49:915-923.
[92]T.Komatsu, K.Aizawa, T.Igarashi, T.Saito.Signal-processing based method for acquiring very high resolution image with multiple cameras and its theoretical analysis[J]. Proc.Inst.Elec. Eng.,1993,140, (1):19-25.
[93]H.J.Trussell, M.R.Civanlar.The landweber iteration and projection onto convex sets[J]. IEEE Transactions on Acoustics, Speech, and Signal Processing,1985, 33(6):1632-1633.
[94]L.Landweber.An iteration formula for Fredholm integral equations of the first kind[J]. Amer.J. Math.1951,73:615-624.
[95]T.Komatsu, T.Igarashi, K.Aizawa, T.Saito.Very high resolution imaging scheme with multiple different-aperture cameras[J]. Signal Processing:Image Communication, Dec.1993,5:511-526.
[96]N.R.Shah, A.Zakhor.Resolution enhancement of color video sequences[J]. IEEE Transactions on Image Processing,1999,8:879-885.
[97]David T.Sandwell.Biharnionic spline interpolation of Geo-3 and Seasat altimeter data[J]. Geophysical Research Letters.1987,14(2):139-142.
[98]Richard Franke. Smooth interpolation of scattered data by local thin plate splines[J]. Comput. Math.Appl.1982,8(4):273-281.
[99]N.Nguyen, P.Milanfar. An efficient wavelet-based algorithm for image superresolution[A]. Proc.Int.Conf.Image processing[C],2000,2:351-354.
[100]TakedaH., Farsiu5., Milanfar P. Kenel regression for image Processing and reconstruction[J]. IEEE Trans. Image Processing,2007,16(2):349-366.
[101]HuniB.R., Sementilli P.J. Description of a Poisson imagery super-resolution algorithm. Astronomical Data Analysis Software and System,1992, 25:196-199.
[102]Sementilli P.J., Nadar M.S., Hunt B.R. Poisson MAP super-resolution estimator with smoothness onstraint[A]. Proceedings of SPIE Neural and Stochastie Metheds in Image and Signal Processing II[C],1993,2032:2-13.
[103]Cheeseman P., Kanefsky B., Kraft R., Stutz J., Hanson R. Super-resolved surface reconstruction from multiple images [A]. NASA Ames Research Centor, Moffett Field, CA, Tech.ReP[C].FIA-94-12,1994.
[104]Sehultz RR, Stevenson RL. Extraction of high-resolution frames from video sequenees[J].IEEE Transactions on Image Processing,1996,5(6):996-1011.
[105]Sehultz RR, Stevenson RL. A Bayesian approach to image expansion for improve definition[J]. IEEE Transactions on Image Processing,1994, 3(3):233-242.
[106]Elad M., Feuer A.Restoration of a single super-resolution image from several bluured, noisy, and under-sampled measured mages[J].IEEE Transactions on Image Processing,1997,6(12):1646-1658.
[107]Hardie R.C., Tuinstra T.R., Bognar J., Bamard K.J., Armstrong E. High resolution image reconstruction from digital video with global and non-global scene motion[A]. Proceedings of the IEEE International Conference on Image Processing[C], Santa Barbara, CA,1997,1:153-156.
[108]Hong M.C., KangM.G., Katsaggelos A.K. A regularized multi-channel restoration apppoach for globally optimal high resolution video sequence[A]. SPIE VCIP[C], San Jose, CA,1997,3024:1306-1317.
[109]Hong M.C., KangM.G., Katsaggelos A.K. An iterative weighted regularized algorithm for improving the resolution of video sequences[A]. In:Proc.Int.Conf. ImageProcessing[C],1997,2:474-477.
[110]Hardie R.C., Bamard K.J., Bognar J.G., Armstrong E.E., Watson E.A. High resolution image reconstruction from sequence of rotated and translated frames and its application to an infrared imaging system[J]. Optical Engineering,1998, 73(1):247-260.
[111]Nguyen N.X. Numerical algorithms for image super-resolution[D]. Califomia:Stanford University,2000.
[112]Nguyen N., Milanfar P., Golub G. Efficient generalized cross-validation with applications to parametric image restoration and resolution enhancement[J]. IEEE Trans. Image Processing,2001,10(9):1299-1308.
[113]Elad M. On the bilateral filter and ways to improve it[J]. IEEE Trans.on Image Processing,2002,11(10):1141-1151.
[114]Farsiu S., Robinson D., Elad M., Milanfar P. Fast and robust multi-frame super-resolution[J]. IEEE Transactions on Image Processing,2004, 13(10):1327-1344.
[115]Capel D., Zisserman A. Super-resolution enhancement of text image sequences[A]. Proc. Intl.Con. Patt.Recog[C],2000,1:600-605.
[116]Kim H., HongK.S. Variational approaches to super-resolution with contrast enhancement and anisotropic diffusion[J]. Journal of Electronic Imaging,2003, 12(2):244-251.
[117]Ng M.K., ShenH.F., lam E.Y, zhangL.P. A total variation regularization based super-resolution reconstruction algorithm for digital video[J]. EURASIPJoumal on Applied signal Processing,2007,7(2):114-129.
[118]M.K.Ozkan, A.M.Tekalp, M.I.Sezan.POCS-based restoration of space-varying blurred images[J].IEEE Transactions on Image Processing,1994,3(4):450-454
[119]StarkH., Oskoui P. High resolution image recovery from image-plane arrays, using conv projeetions[J].J.Opt.Soc.Am.A,1989,6(11):1715-1726.
[120]Youla D.C.Image restoration by the method of convex projections:part 1 theory[J]. IEEE Transactions on Medical Imaging,1982,10(2):81-94.
[121]A.J.Patti, M.I.Sezan, A.M.Tekalp.Superresolution video reconstruction with arbitrary sampling lattices and nonzero aperture time[J].IEEE Transactions on Image Processing,1997,6(8):1064-1076.
[122]Tekalp A.M., Ozkan M.K., Sezan M.I. High-resolution image reconstruction from lower-resolution image sequences and space varying image restoration[A]. Proc.IEEE Int. Conf Aeousties, Speech and Signal Processing(ICASSP)[C], SanFraneisco, CA.,1992,169-172.
[123]J.Patti, M.I.Sezan, A.M.Tekalp.Robust methods for high-quality stills from interlaced video in the presence of dominant motion[J].IEEE Transactions on Circuits and Systems for Video Technology,1997,7(2):328-342.
[124]P.E.Eren, M.I.Sezan, A.M.Tekalp.Robust, object-based high-resolution image reconstruction from low-resolution video[J].IEEE Transactions on Image Processing,1997,6(10):1446-1451.
[125]Tokiu, A.T.Erdem, M.I.Sezan, A.M.Tekalp.Tracking motion and intensity variations using hierarchical 2-D mesh modeling for synthetic object transfiguration[J].Graphical Models and Image Processing.1996,58(6):553-573.
[126]B.C.Tom, A.K.Katsaggelos An iterative algorithm for improving the resolution of video sequences[A]. Proc.1996 SPIE Conf. Visual Communications and Image Processing[C], Orlando, FL, Mar.996.1430-1438.
[127]A.J.Patti, Y.Altunbasak.Artifact reduction for set theoretic super resolution image reconstruction with edge adaptive constraints and higher-order interpolants.IEEE[J].Transactions on Image Processing,2001,10(1):179-186
[128]Mallats.著.信号处理的小波导引(第2版)[M].杨力华,戴道清,黄文良,湛秋辉译.北京：机械工业出版社,2002.
[129]Li J., Sheng Y.L. Wavelet domain super-resolution reconstru ctionofinfrared image sequences[A]. Proceedings of SPIE[C],2001,4385:108-116.
[130]NgUyen N., Milanfar P. A wavelet-based interpolation-restoration method for super-resolution[J]. Circuits systems Signal Process,2000,19(4):321-338.
[131]Fadili M.J., StarekJ.L., Murtagh F. Inpainting and zooming using sparse representations[J]. The Computer Journal,2009,52(1):64-79.
[132]Jiji C.V., Chaudhuri S. Single-frame image super-resolution through contourlet learning[J]. EURASIP Journal on Applied signal Processing,2006,1:1-11.
[133]张地,杜明辉.超分辨率图像重建边缘振荡的高效去除算法[J].信息与电子工程,2004,4(4)：81-85.
[134]相里斌,李英才,刘良云.超分辨率图像重构技术的仿真实验研究[J].中国图象图形学报,2001,6(7)：629-635.
[135]王程,王润生.基于MAP框架的图像序列超分辨率和模板匹配[J].计算机学报,2003,26(8)：961-967.
[136]邵凌,丁佩律,张立明,胡波.从多帧低分辨率图像序列中获取高分辨率图像的算法研究[J].电子学报,2002,30(1)：58-61.
[137]邵凌,丁佩律,张立明,胡波.重建高分辨率图像的实时串行迭代算法[J].红外与毫米波学报,2002,21(2)：104-108.
[138]苏秉华,金伟其,牛丽红,刘广荣,刘明奇.基于Markov约束的泊松最大后验概率超分辨率图像复原法[J].光子学报,2002,31(4)：492-496.
[139]洪功义,姜显明.基于图像配准的POCS超分辨率图像重建[J].计算机仿真,2004,21(6)：145-147.
[140]黄丽,庄越挺,苏从勇,吴飞.基于多尺度和多方向特征的人脸超分辨率算法[J].计算机辅助设计与图形学学报,2004,16(7)：953-961.
[141]赵书斌,彭思龙.基于小波域HMT模型的图像超分辨率重建[J].计算机辅助设计与图形学学报,2003,15(11)：1347-1352.
[142]张新明,沈兰荪.在小波变换域内实现图像的超分辨率复原[J].计算机学报,2003,26(9)：1183-1189.
[143]Jiang Z.D., Lin H., Bao H.J., Ma L.Z. A super-resolution methed with EWA[J]. Journal of Computer Science and Technology,2003,18(6):822-832.
[144]汪雪林,文伟,彭思龙.基于小波域局部高斯模型的图像超分辨率[J].中国图象图形学报,2005,28(6)：1006-1012.
[145]程燕.图像超分辨率重建关键技术的研究[D].上海：上海交通大学,2007.
[146]潘逢治,张立明.用神经网络恢复残差的图像超分辨率算法[J].电子学报,2004,32(1)：161-165.
[147]韩玉兵.图像及视频序列的超分辨率重建[D].南京：东南大学,2005.
[148]郭晓新.超分辨率重建问题的研究[D].吉林：吉林大学,2005.
[149]教育部科技发展中心.哈工大开创性成果让卫星图像更清晰.http://www.cutech.edu.cn/cn/zggx/zxzx/2006/09/1179971253618210.htm.
[150]ZhangJian, Fan Xiaoping, Huang Cailun, A Method of Super-Resolution
Image Restoration Based on Separation[A], Proceedings of the 26th Chinese Control Conference[C],2007,275-277.
[151]张剑,田岩,柳健.一种基于分离思想的超分辨率复原方法[J].华中科技大学学报(自然科学版)2003,31(8)：27-28,31.
[152]Michael Elad, Yacov Hel-or, A Fast Super-resolution Reconstruction Algorithm for Pure Translational Motion and Common Space-invariant Blur[J]. IEEE Transactions on Image Processing,2001,10(8):1187-1193.
[153]Yubing Han, Feng Shu, Qingchuan Zhang, Image super-resolution reconstruction based on adaptive interpolation norm regularization[J]. Intelligent Signal Processing and Communication Systems, P.698-701,2007.
[154]ZhangJian, Fan Xiaoping, Huang Cailun, Tian Yuan, Multi-spectral Image Super-Resolution Reconstruction Based on B-spline Interpolation[A], SPIE Sixth International Symposium on Multispectral Image Processing and Pattern Recognition[C].2009,7494:165-171.
[155]刘洪臣,杨旭强,冯勇, 亚像元成像系统B样条插值方法[J].光电工程.2006,33(2)：90-94.
[156]Farsiu S, Elad M, Milanfar P. Multiframe demosaicing and super-resolution of color images[J].IEEE Transaction on Image Processing,2006,15 (1):141-160.
[157]A. M. Tekalp, M. K. Ozkan, and M. I. Sezan. High-resolution image reconstruction from lower-resolution image sequences and space-varying image restoration[A]. ICASSP 1992 [C], San Francisco, vol. Ⅲ:169-172.
[158]A.J.Patti. M.I.Sezan, and A.M.Tekalp, High-resolution standards conversion of low-resolution video[A], Proc. IEEE. Int. conf. Acoustics, Speech and Signal Processing (ICASSP)[C],1995, Vol.Ⅱ:2197-2200.
[159]R. R. Schultz and R. L. Stevenson, Improved definition video frame enhancement[A], IEEE Int. Conf. Acoustics, Speech, and Singal Processing (ICASSP)[C],1995, Vol.Ⅳ:2169-2172.
[160]邹谋炎,反卷积和信号复原[M],北京,国防工业出版社,2001.
[161]Zhang Jian, Fan Xiaoping, Huang Cailun, On Evaluation Criterion of Image Super-Resolution Reconstruction[A], Proceedings of IEEE ICICIC07[C],2007, 177-182.
[162]A.K Katsaggelos and S.N. Efstratiadis, A class of iterative signal restoration algorithm[J].IEEE Trans. Acoust.,Speech,Signal Processing,2000, Vol.38:778-786