• Laser & Optoelectronics Progress
  • Vol. 52, Issue 2, 20004 (2015)
Chen Jian1、2、3、*, Gao Huibin1, Wang Weiguo1, and Bi Xun1、2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
  • show less
    DOI: 10.3788/lop52.020004 Cite this Article Set citation alerts
    Chen Jian, Gao Huibin, Wang Weiguo, Bi Xun. Methods and Applications of Image Super-Resolution Restoration[J]. Laser & Optoelectronics Progress, 2015, 52(2): 20004 Copy Citation Text show less
    References

    [1] M R Banham, A K Katsaggelos, et al.. Digital image restoration[J]. IEEE Signal Processing Magazine, 1997, 14(2): 24-41

    [2] H Trussel, M Civanlar. Feasible solution in signal restoration[J]. IEEE Trans Accoust Speech Signal Processing, 1984, ASSP-32: 201-212.

    [3] B R Hunt. Super-resolution of images: Algorithms, principles, performance[J]. International J Imaging Systems Technol, 1995, 6(4): 297-304.

    [4] X Gao, K Zhang, D Tao, et al.. Joint learning for single-image super-resolution via a coupled constraint[J]. IEEE Trans Image Process, 2012, 21(2): 469-480.

    [5] H He, W C Siu. Single image super-resolution using Gaussian process regression[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2011. 449-456.

    [6] K I Kim, Y Kwon. Single-image super-resolution using sparse regression and natural image prior[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010, 32(6): 1127-1133.

    [7] Y W Tai, S Liu, M S Brown, et al.. Super resolution using edge prior and single image detail synthesis[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2010. 2400-2407.

    [8] F Ahmed, S C Gutafsou, M A Karim. High-fidelity image interpolation using radial basis function neural networks[C]. Proc IEEE National Aerospace and Electronics Conference, 1995, 2: 588-592.

    [9] N Plaziac. Image interpolation using neural networks[J]. IEEE Trans on image Processing, 1999, 8(11): 1647-1651.

    [10] F M Candlneia, J C Principle. Super resolution of images based on local correlations[J]. IEEE Trans Neural Networks, 1999, 10(2): 372-380.

    [11] R R Schultz, R L Stevenson. A Bayesian approach to image expansion for improved definition[J]. IEEE Trans on Image Processing, 1994, 3(3): 233-242.

    [12] X Li, M T Orchard. New edge-directed interpolation[J]. IEEE Trans Image Processing, 2001, 10(10): 1521-1527.

    [13] R Zeyde, M Elad, M Protter. On Single Image Scale-Up Using Sparse-Representations[M]. Berlin Heidelberg: Springer Press, 2012. 711-730.

    [14] D Glasner, S Bagon, M Irani. Super-resolution from a single image[C]. IEEE Conference on Computer Vision, 2009. 349-356.

    [15] M K Ng, N K Bose. Mathematical analysis of super-resolution methodology[J]. IEEE Signal Processing Magazine, 2003, 20(3): 62-74.

    [16] N K Bose. Multi-Dimensional Systems Theory and App1ications[M]. Holland: Kluwer Academic Publishers Press, 2003.

    [17] R Y Tsai, T Huang. Multi frame image restoration and registration[J]. Advances in Computer Vision and Image Processing, 1984, 1(2): 317-339.

    [18] A M Tekalp, M K Ozkan, M L Sezan. High-resolution image reconstruction for lower-resolution image restoration[C]. Proceedings of the IEEE international Conference on Acoustics, Speech and Signal Processing, 1992, 3: 169-172.

    [19] S P Kim, W Y Su. Recursive high- resolution reconstruction of blurred multi- frame images[J]. IEEE Trans Image Processing, 1993, 2(4): 534-539.

    [20] M Elad, A Feuer. Super- resolution restoration of an image sequence: adaptive filtering approach[J]. IEEE Trans Image Processing, 1999, 8(3): 387-395.

    [21] C E Davila. Efficient recursive total least squares algorithms for FIR adaptive filtering[J]. IEEE Trans Signal Processing, 1994, 42(2): 268-280.

    [22] N X Ngugen. Numerical Algorithm for Image Super Restoration[D]. California: Stanford University, 2000.

    [23] Zhou Fang. A review of super-resolution image restoration[J]. Automation and Instrument, 2006, (1): 10-14.

    [24] F M Candlneia, J C Principle. Super resolution of images based on local correlations[J]. IEEE Trans Neural Networks, 1999, 10(2): 372-380.

    [25] Zhang Xinming, Shen Lansun. The development of super- resolution restoration from image sequence[J]. Control Technology, 2002, 21(5): 33-35.

    [26] H Ur, D Gross. Improved resolution from sub-pixel shifted pictures[J]. CVGIP: Graphical Models and Image Processing, 1992, 54(2): 181-186.

    [27] A Papoulis. Generalized sampling expansion[J]. IEEE Trans Circuits Syst, 1977, 24(11): 652-654.

    [28] J L Brown. Multi-channel sampling of low pass signals[J]. IEEE Trans Circuits Syst, 1981, CAS-28: 101-106.

    [29] R C Hardie, K J Barnard, E E Armstrong. Joint MAP registration and high-resolution image estimation using a sequence of under-sampled images[J]. IEEE Trans Image Processing, 1997, 6(12): 1621-1633.

    [30] N Nguyen. Numerical Algorithms for Image Super-Resolution[D]. California:Stanford University, 2000.

    [31] N Nguyen, P Milanfar. A wavelet-based interpolation-restoration method for super-resolution[J]. Circuits Systems Signal Process, 2000, 19(4): 321-338.

    [32] S Lertrattanapanich. Super- Resolution from Degraded Image Sequence Using Spatial Tessellations and Wavelets[D]. University Park: Pennsylvania State University, 2003.

    [33] A J Patti, M Sezan, A M Tekalp. A new motion compensated reduced order model kalman filter for space- varying restoration of progressive and interlaced video[J]. IEEE Trans Image Processing, 1998, 7(4): 543-554.

    [34] M Elad, A Feuer. Super- resolution restoration of image sequence[J]. IEEE Trans Pattern Anal. Machine Intelligence, 1999, 21(9): 817-834.

    [35] M Elad, A Feuer. Super-resolution reconstruction of continuous image sequences[C]. International Conference on Image Processing, Kobe, Japan, 1999. 459-463.

    [36] M S Alam, J G Bognar, R C Hardie, et al.. Infrared image registration and high-resolution reconstruction using multiple translationally shifted aliased video frames[J]. IEEE Trans Instrumentation Measurement, 2000, 49(5): 915-923.

    [37] B R Frieden, H G Aumann. Image reconstruction from multiple 11-D scans using filtered localized projection[J]. Appl Optics, 1987, 26(3): 223-226.

    [38] M Irani, S Peleg. Improving resolution by image registration[J]. CVGIP: Graphical Models and Image Processing, 1991, 53(3): 231-239.

    [39] Guo Weiwei, Zhang Pinzheng. Super-resolution image reconstruction with iterative back projection algorithm[J]. Journal of Frontiers of Computer Science and Technology, 2009, 3(3): 321-329.

    [40] Tan Fengqing, He Xiaohai, Chen Weilong, et al.. A video super-resolution reconstruction method based on sub-pixel registration[J]. Journal of Optoelectronics·Laser, 2009, 20(7): 972-976.

    [41] Zhang Yongyu, Li Cuihua, Yu Liba, et al.. IBP super-resolution reconstruction based on improvement approach of Keren registration method[J]. Journal of Xiamen University, 2012, 51(4): 686-69.

    [42] S Maan, R W Picard. Virtual bellows: Constructing high quality stills from video[C]. Proc of International Conference on Image Processing, Austin, TX, 1994, 1: 363-367.

    [43] B C Tom, A K Katsaggelos. Resolution enhancement of video sequences using motion compensation[C]. Proc of IEEE Int. Conf Image Processing, Lausanne, Switzerland, 1996, 1: 713-716.

    [44] D C Youla, H Webb. Image restoration by the method of convex projections: Part I, theory[J]. IEEE Transactions on Medical Imaging, 1982, 1(2): 81-94.

    [45] H Stark, P Oskoui. High resolution image recovery from image-plane arrays, using convex projection[J]. JOSA A, 1989, 6(11): 1715-1726.

    [46] M Tekalp, M K Ozkan, M I Sezan. High-resolution image reconstruction from lower-resolution image sequences and space varying image restoration[C]. IEEE international Conference on Acoustics, Speech and Signal Processing, 1992, 3: 169-172.

    [47] B K Gunturk, Y Altunbasak, R M Mersereau. Super- resolution reconstruction of compressed video using transformdomain statistics[J]. IEEE Trans Image Processing, 2004, 13(1): 33-43.

    [48] Huang Hua, Kong Lingli, Qi Chun, et al.. Super-resolution image reconstruction based on projections onto convex sets and line process modeling[J]. Journal of Xi′an Jiaotong University, 2003, 37(10): 1059-1062.

    [49] Zhu Xiang, Yuan Jie, Du Sidan. Recovery of JPEG compressed image sequence[J]. Journal of Electronics and Information Technology, 2007, 29(8): 1841-1844.

    [50] Xiao Chuangbai, Duan Juan, Yu Jing. POCS super-resolution reconstruction from image sequences[J]. Journal of Beijing University of Technology, 2009, 35(1): 108-113.

    [51] Zhang Xian, Xu Kun, Li Yong. Remote sensing image super-resolution based on POCS and out-of-core[J]. Journal of Tsinghua University, 2010, 50(10): 1743-1746.

    [52] Zhang Yan, Li Xianying, Man Yiyun. Remote sensing images upsampling based on projection onto convex sets and complex wavelet packet transfer[J]. Chinese Journal of Computers, 2011, 34(3): 482-488.

    [53] 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[C]. Proc IEEE Int Conf Image Processing, Austin, TX, 1994, 1: 343-347.

    [54] J Patti, M Sezan, A M Tekalp. Super-resolution video reconstruction with arbitrary sampling lattices and nonzero aperture time[J]. IEEE Trans Image Processing, 1997, 6(8): 1064-1076.

    [55] J Patti, M Sezan, A M Tekalp. Robust methods for high-quality stills from interlaced video in the presence of dominant motion[J]. IEEE Trans Circuits and Systems for Video technology, 1997, 7(2): 328-342.

    [56] J Patti, Y Altunbasak. Artifact reduction for set theoretic super resolution image reconstruction with edge adaptive constraints and higher-order interpolants[J]. IEEE Trans Image Processing, 2001, 10(1): 179-186.

    [57] B C Tom, A K Katsaggelos. An Iterative Algorithm for Improving the Resolution of Video Sequence[A]. Proc SPIE Conf. Visual Communication and Image Processing, Orlando, FL, 1995. 1430-1438.

    [58] R R Sehultz, R L Stevenson. A Bayesian approach to image expansion for improved definition[J]. IEEE Transactions on Image Processing, 1994, 3(2): 233-242.

    [59] R C Hardie, K J Bamard, E E Armstrong. Joint MAP registration high-resolution image estimation using a sequence of under sampled image[J]. IEEE Transactions on Image Processing, 1997, 6(12): 1621-1633.

    [60] P Cheeseman, B Kanefsky. Super- resolved surface reconstruction from multiple images[R]. NASA Ames Research Center, Moffett Field, CA, Tech ReP FIA-94-12, 1994.

    [61] B R Hunt, P J Sementilli. Description of a Poisson imagery super-resolution algorithm[C]. Astronomical Data Analysis Software and System I, California, USA, 1992, 25: 196-199.

    [62] P J Sementilli, M S Nadar, B R Hunt. Poisson MAP super-resolution estimator with smoothness constraint[C]. Proceedings of SPIE Neural and Stochastic Methods in Image and Signal Processing II, 1993, 2032: 2-13.

    [63] G K Chantas, N P Galatsanos, N A Woods. Super- resolution based on fast registration and maximum a posteriori reconstruction[J]. IEEE Transactions on Image Processing, 2007, 16(7): 1821-1830.

    [64] S P Belekos, N P Galatsanos, A K Katsaggelos. Maximum a posteriori video super-resolution using a new multichannel image prior[J]. IEEE Transactions on Image Processing, 2010, 19(6): 1451-1464.

    [65] L J Karam, N G Sadaka. An Efficient selective perceptual- based super- resolution estimator[J]. IEEE Trans Image Processing, 2011, 20(12): 3470-3481.

    [66] D Wallach, F Lamare. Super-resolution in respiratory synchronized positron emission tomography[J]. IEEE Transactions on Medical Imaging, 2012, 31(2): 438-448.

    [67] M Irani, S Peleg. Motion analysis for image enhancement, resolution, occlusion and transparency[J]. Journal of Visual Communication and Image Representation, 1993, 4(4): 324-336.

    [68] M Irani, S Peleg. Super resolution from image sequences[C]. Piscataway, NJ, USA: Proceedings of international Conference on Pattern Recognition, 1990. 115-120.

    [69] Xian Haiying, Fu Zhizhong, Wan Qun, et al.. Super resolution algorithm based on non- redundant information[J]. Chinese Journal of Radio Science, 2012, 27(2): 216-221.

    [70] Wang Jing, Zhang Shiping, Sun Quansen, et al.. MAP based remote sensing image super- resolution with frequency domain correction[J]. Journal of Southeast University, 2010, 40(1): 84-88.

    [71] Han Yubing, Wu Lenan. Super resolution reconstruction of video sequence based on adaptive filter[J]. Chinese Journal of Computer, 2006, 29(4): 642-647.

    [72] Han Hua, Wang Hongjian, Peng Silong. A new super-resolution algorithm for a single image based on local structure similarity[J]. Journal of Computer Aided Design and Computer Graphics, 2005, 17(5): 941-947.

    [73] Chen Hua, Jin Weiqi, Wang Xia, et al.. A method of restoration for the 3D image of wide- field microscope based on wavelet packet analysis denoising[J]. Transactions of Beijing Institute of Technology, 2006, 26(1): 72-75.

    [74] M Elad, A Feuer. Restoration of a single super-resolution image from several blurrd, noisy and under sampled measured images[J]. IEEE Trans Image Processing, 1997, 6(12): 1646-1658.

    [75] Su Binghua, Jing Weiqi. POCS-MPMAP based super-resolution image restoration[J]. Acta Photonica Sinica, 2003, 32(4): 502-504.

    [76] D P Capel. Image Mosaicing and Super-Resolution[D]. London: University of Oxford, 2001.

    [77] M Elad. On the bilateral fi1ter and ways to improve it[J]. IEEE Transactions on Image Processing, 2002, 11(10): 1141-1151.

    [78] D Barash. Bilateral filtering and anisotropic diffusion: Towards a unified viewpoint[C]. Hewlett-Packard Laboratories Technical Report, 2000. 18.

    [79] S Farsiu, M D Robinson. Fast and robust multiframe super resolution[J]. IEEE Transactions on Image Processing, 2004, 13(10): 1327-1344.

    [80] C Tomasi, R Manduchi. Bilateral filtering for gray and color images[C]. Proc of the 6th international Conference on Computer Vision, 1998. 839-846.

    [81] G Gilboa, N Soehen, Y Y Zeevi. Forward- and- backward diffusion processes for Adaptive image enhancement and denoising[J]. IEEE Trans Image Processing, 2002, 11(7): 689-703.

    [82] E Shechtman, Y Caspi, M Irani. Space-time super-resolution[J]. IEEE Trans Pattern Analysis and Machine Intelligence, 2005, 27(4): 531-545.

    [83] H Kim, K S Hong. Variational approaches to super-resolution with contrast enhancement and anisotropic diffusion[J]. J Electron Imaging, 2003, 12(2): 244-251.

    [84] A Zomet, S Peleg. Multi-sensor super-resolution[C]. Proceedings of the IEEE Workshop on applications of computer Vision, 2001. 27-31.

    [85] N Nguyen, P Milanfar, G Golub. A computationally efficient super resolution image Reconstruction algorithm[J]. IEEE Trans Image Processing, 2001, 10(4): 573-583.

    [86] P D Wirawan, H Maitre. Multi-channel high resolution blind image restoration[C]. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing, 1989. 3229-3232.

    [87] S Baker, T Kanade. Limits on super-resolution and how to break them[C]. Proceedings of IEEE Conference Computer Vision and Patten Recognition, 2000. 372-379.

    [88] Z C Lin, H Y Shum. Fundamental limits of reconstruction- based super- resolution algorithms under local translation [J]. IEEE Trans Pattern Analysis and Machine Intelligence, 2004, 26(1): 83-97.

    [89] J Sun, Z Xu, H Y Shum. Image super-resolution using gradient profile prior[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2008. 1-8.

    [90] T Tung, S Nobuhara, T Matsuyama. Simultaneous super-resolution and 3D video using graph-cuts[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2008. 1-8.

    [91] K Nguyen, C Fookes, S Sridharan, et al.. Quality- driven super- resolution for less constrained iris recognition at a distance and on the move[J]. IEEE Trans Information Forensics and Security, 2011, 6(4): 248-1258.

    [92] T K Nguyen, C B Fookes, S Sridharan, et al.. Feature- domain super- resolution for IRIS recognition[C]. Proceedings of The 18th International Conference on Image Processing, 2011. 3258-3261.

    [93] C Liu, D Sun. A Bayesian approach to adaptive video super resolution[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2011. 209-216.

    [94] S Wang, D Zhang, Y Liang, et al.. Semi- coupled dictionary learning with applications to image super- resolution and photo-sketch synthesis[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2012. 2216-2223.

    [95] J Yang, Z Wang, Z Lin, et al.. Coupled dictionary training for image super-resolution[J]. IEEE Trans Image Processing, 2012, 21(8): 3467-3478.

    [96] J Yang, J Wright, T S Huang, et al.. Image super-resolution via sparse representation[J]. IEEE Trans Image Processing, 2010, 19(11): 2861-2873.

    [97] J Wang, S Zhu, Y Gong. Resolution enhancement based on learning the sparse association of image patches[J]. Pattern Recognition Letters, 2010, 31(1): 1-10.

    [98] Y Hu, K M Lam, G Qiu, et al.. From local pixel structure to global image super- resolution: a new face hallucination framework[J]. IEEE Trans Image Processing, 2011, 20(2): 433-445.

    [99] H Zhang, J Yang, Y Zhang, et al.. Non-Local Kernel Regression for Image and Video Restoration[M]. Berlin Heidelberg: Springer Press, 2010. 566-579.

    [100] Chen Jian. Research on Infrared Dim- Small Target Super- Resolution Restoration Arithmetic Based on POCS[D]. Changchun:University of Chinese Academy of Sciences, 2014.

    CLP Journals

    [1] Wang Min, Liu Kexin, Liu Li, Yang Runling. Super-Resolution Reconstruction of Image Based on Optimized Convolution Neural Network[J]. Laser & Optoelectronics Progress, 2017, 54(11): 111005

    [2] Gao Meijing, Xu Wei, Wu Weilong, Wang Jingyuan. Optical Micro-Scanning X-Ray Real-Time Imaging Method[J]. Laser & Optoelectronics Progress, 2016, 53(5): 51102

    [3] Lin Liangkui, Wang Shaoyou, Wang Tiebing. Simulation and Analysis of Point Target Detection Performance for Infrared Scanning Over-Sampling System[J]. Acta Optica Sinica, 2016, 36(5): 528001

    Chen Jian, Gao Huibin, Wang Weiguo, Bi Xun. Methods and Applications of Image Super-Resolution Restoration[J]. Laser & Optoelectronics Progress, 2015, 52(2): 20004
    Download Citation