Volume 7 Issue 6
Nov.  2014
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CHEN Jian, GAO Huibin, WANG Weiguo, ZHANG Zhendong, LU Ming. Correlation theory of super-resolution restoration method[J]. Chinese Optics, 2014, 7(6): 897-910. doi: 10.3788/CO.20140706.0897
Citation: CHEN Jian, GAO Huibin, WANG Weiguo, ZHANG Zhendong, LU Ming. Correlation theory of super-resolution restoration method[J]. Chinese Optics, 2014, 7(6): 897-910. doi: 10.3788/CO.20140706.0897

Correlation theory of super-resolution restoration method

doi: 10.3788/CO.20140706.0897
  • Received Date: 01 Oct 2014
  • Rev Recd Date: 06 Nov 2014
  • Publish Date: 25 Nov 2014
  • Firstly, the basic concepts and theories of super-resolution restoration method are introduced. Secondly, some applications focused on common method of super-resolution restoration are summarized. Their theoretical basis, advantages and disadvantages, and scope of applications are exhaustively analyzed. Finally, the future development of super-resolution restoration method is prospected. Overall, the super-resolution restoration methods are divided into frequency domain method and space domain method. Frequency domain recovery method is simple in principle and easy in calculation. But its motion model is shift model and doesn't have a general. Meanwhile it is difficult to use the priori information of the image to help super-resolution restoration. With space domain recovery method, a complex motion model can be easily established considering almost all of the imaging degradation factors, including noise, down sampling, fuzzy caused by non-zero aperture, degradation of optical system, and motion blur. As the same time, we could also add more perfect priori knowledge. Compared to the frequency domain method, space domain super-resolution restoration model is more close to actual degradation processes and is currently the most widely used super-resolution restoration method.

     

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  • [1] 李衍达,常迥.信号重构理论及其应用[M]. 北京:清华大学出版社, 1991. LI Y D,CHANG J. Signal Reconstruction Theory and Its Application[M]. Beijing:Tsinghua University Press,1991.(in Chinese)
    [2] KIM S P,SU W Y. Recursive high-resolution reconstruction of blurred multi-frame images[J]. IEEE,1993,2(4):534-539.
    [3] KIM S P,BOSE N K,VALENZUELA H M. Recursive reconstruction of high resolution image from noisy under sampled multiframes[J]. IEEE,1990,38(6):1013-1027.
    [4] SU W,KIM S P. High-resolution restoration of dynamic image sequences[J]. International J. Imaging Systems and Technology,1994,5(4):330-339.
    [5] BOSE N K,KIM H C. Recursive implementation of total least squares algorithm for image reconstruction from noisy, under sampled multiframes[J]. IEEE,1993,1:269-272.
    [6] DAVILA C E. Recursive total least squares algorithms for adaptive filtering[J]. IEEE,1991,3:1853-1856.
    [7] KEREN D,PELEG S,BRADA R. Image sequence enhancement using sub-pixel displacements[J]. IEEE,1988,1:742-746.
    [8] AIZAWA K,KOMATSU T,SAITO T. Acquisition of very high resolution images using stereo cameras[J]. IEEE,1991,1:318-328.
    [9] TEKALP A M,OZKAN M K,et al.. High-resolution image reconstruction from lower-resolution image sequences and space-varying image restoration[J]. IEEE,1992,3:169-172.
    [10] NGUYEN N,MILANFAR P. A wavelet-based interpolation-restoration method for super-resolution[J]. Circuits Systems Signal Process,2000,19(4):321-338.
    [11] ELAD M,FEUER A. Super-resolution restoration of an image sequence:adaptive Filtering approach[J]. IEEE,1999,8(3):387-395.
    [12] ALAM M S,BOGNAR J G,HARDIE R C,et al.. Infrared image registration and high-resolution reconstruction using multiple translationally shifted aliased video frames[J]. IEEE,2000,49(5):915-923.
    [13] IRANI M,PELEG S. Improving resolution by image registration[J]. CVGIP:Graphical Models and Image Processing,1991,53:231-239
    [14] 郭伟伟,章品正. 基于迭代反投影的超分辨率图像重建[J]. 计算机科学与探索,2009,3(3):321-329. GUO W W,ZHANG P ZH. Super-resolution image reconstruction with iterative back projection algorithm[J]. J. Frontiers of Computer Science and Technology,2009,3(3):321-329.(in Chinese)
    [15] 覃凤清,何小海,陈为龙,等. 一种基于子像素配准视频超分辨率重建方法[J]. 光电子·激光,2009,20(7):972-976. TAN F Q,HE X H,CHEN W L,et al.. A video super-resolution reconstruction method based on sub-pixel registration[J]. J. Optoelectronics Laser,2009,20(7):972-976.(in Chinese)
    [16] 张永育,李翠华,余礼钹,等. 基于Keren改进配准算法的IBP超分率重建[J]. 厦门大学学报(自然科学版),2012,51(4):686-69. ZHANG Y Y,LI C H,YU L B,et al.. IBP super-resolution reconstruction based on improvement approach of Keren registration method[J]. J. Xiamen University,2012,51(4):686-69.
    [17] MAAN S,PICARD R W. Virtual bellows: Constructing high quality stills from video. Proc. of International Conference on Image Processing,Austin,TX,1994,1:363-367.
    [18] TOM B C,KATSAGGELOS A K. Resolution enhancement of video sequences using motion compensation. Proc of IEEE Int. Conf Image Processing,Lausanne,Switzerland,1996,1:713-716.
    [19] YOULA D C,WEBB H. Image restoration by the method of convex projections: part I,theory[J]. IEEE,1982,2:81-94.
    [29] STARK H,OSKOUI P. High resolution image recovery from image-plane arrays, using convex projection[J]. JOSA A,1989,6:1715-1726.
    [21] 黄华,孔玲莉,齐春,等. 基于凸集投影和线过程模型的超分辨率图像重建[J].西安交通大学学报,2003,37(10):1059-1062. HUANG H,KONG L L,QI CH,et al.. Super-resolution image reconstruction based on projections onto convex sets and line process modeling[J]. J. Xi'an Jiaotong University,2003,37(10):1059-1062.(in Chinese)
    [22] 肖创柏,段娟,禹晶. 序列图像的POCS超分辨率重建方法[J]. 北京工业大学学报,2009,35(1):108-113. XIAO CH B,DUAN J,YU J. POCS super-resolution reconstruction from image sequences[J]. J. Beijing University of Technology,2009,35(1):108-113.(in Chinese)
    [23] PATTI J,SEZAN M,TEKALP A M. High-resolution image reconstruction from a low-resolution image sequence in the presence of time-varying motion blur. Proc IEEE Int. Conf. Image Processing, Austin,TX,1994,1:343-347.
    [24] PATTI J,SEZAN M,TEKALP A M. Super-resolution video reconstruction with arbitrary sampling lattices and nonzero aperture time[J]. IEEE,1997,6(8):1064-1076.
    [25] PATTI J,SEZAN M,TEKALP A M. Robust methods for high-quality stills from interlaced video in the presence of dominant motion[J]. IEEE,1997,7(2):328-342.
    [26] SCHULTZ R R,STEVENSON R L. A Bayesian approach to image expansion for improved definition [J]. IEEE,1994,3(3):233-241.
    [27] HARDIE R C,BARNARD K J,ARMSTRONG E E. Joint MAP registration and high-resolution image estimation using a sequence of under-sampled images[J]. IEEE,1997,6(12):1621-1633.
    [28] 鲜海莹,傅志中,万群,等. 基于非冗余信息的超分辨率算法[J]. 电波科学学报,2012,27(2):216-221. XIAN H Y,FU ZH ZH,WAN Q,et al.. Super resolution algorithm based on non-redundant information[J]. Chinese J. Radio Science,2012,27(2):216-221.(in Chinese)
    [29] 王静,章世平,孙权森,等. 基于MAP估计的遥感图像频域校正超分辨率算法[J]. 东南大学学报,2010,40(1):84-88. WANG J,ZHANG SH P,SUN Q S,et al.. MAP based remote sensing image super-resolution with frequency domain correction[J]. J. Southeast University,2010,40(1):84-88.(in Chinese)
    [30] ELAD M,FEUER A. Restoration of a single super-resolution image from several blurrd, noisy and under sampled measured images[J]. IEEE,1997,6(12):1646-1658.
    [31] HONGJIU T,XINJIAN T,JIAN L,et al. Super resolution remote sensing image processing algorithm based on wavelet transform and interpolation[J]. SPIE,2003,4898:259-263.
    [32] HERTZMANN A,ANALOGIES A. Computer Graphics[M]. New York:Siggraph,ACM Press,2001.
    [33] BAKER S,KANADE T. Limits on super-resolution and how to break them[J]. IEEE,2000,1:372-379.
    [34] GUNTURK B K,ALTUNBASAK Y,MERSEREAU R M. Multiframe resolution enhancement methods for compressed video[J]. Signal Processing Letters,2002,9:170-174.
    [35] 陈健. 基于POCS的红外弱小目标超分辨率复原算法研究.长春:中国科学院大学,2014. CHEN J. Research on infrared dim-small target super-resolution restoration arithmetic based on POCS. Changchun:University of Chinese Academy of Sciences,2014.(in Chinese)

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