Improved Algorithm of Remote Sensing Images Super-Resolution Based on Nonparametric Bayesian

Li Li; Lichun Sui; Mingtao Ding; Zhenyin Yang; Junmei Kang; Shuo Zhai

doi:10.3788/LOP55.032801

[1] Guo H D[M]. Perception of heaven and earth: acquisition and processing technology, 1-20(2000).

[2] Cheng X J, Cheng X L, Hu M J et al. Buildings detection and contour extraction by the fusion of aerial images and LIDAR point cloud[J]. Chinese Journal of Lasers, 43, 0514002(2016).

[3] Xu Q[M]. Remote sensing images fusion and resolution enhancement technology, 1-34(2007).

[4] Jiang C. The spatial resolution improvement of optical remote sensing images with regularization methods[D]. Wuhan: Wuhan University, 1-23(2015).

[5] Zhong J S. Research on super-resolution reconstruction algorithm of optical remote sensing images based on sparse representation[D]. Nanjing: Nanjing Normal University, 1-9(2013).

[6] Polatkan G, Zhou M Y, Carin L et al. A Bayesian nonparametric approach to image super-resolution[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37, 346-358(2015). http://www.ncbi.nlm.nih.gov/pubmed/26353246

[7] Yang C, Yang B, Huang G Y. Remote sensing image fusion based on multispectral image super-resolution[J]. Laser & Optoelectronics Progress, 53, 021001(2016).

[8] Harris J. Diffraction and resolving power[J]. Journal of the Optical Society of America, 54, 931-936(1964).

[9] Farsiu S, Robinson M, Elad M et al. Fast and robust multi-frame super resolution[J]. IEEE Transactions on Image Processing, 13, 1327-1344(2004). http://www.ncbi.nlm.nih.gov/pubmed/15462143

[10] Bishop C. Bayesian image super-resolution[C]. Advances in Neural Information Processing Systems, 15, 1303-1310(2003).

[11] Stark H, Oskoui P. High-resolution image recovery from image-plane arrays, using convex projections[J]. Journal of the Optical Society of America A, 6, 1715-1726(1989). http://www.ncbi.nlm.nih.gov/pubmed/2585170

[12] Shen H F, Li P X, Zhang L P. Adaptive regularized MAP super-resolution reconstruction method[J]. Geomatics and Information Science of Wuhan University, 31, 949-952(2006).

[13] Irani M, Peleg S. Improving resolution by image registration[J]. CVGIP: Graphical Models and Image Processing, 53, 231-239(1991). http://www.sciencedirect.com/science/article/pii/104996529190045L

[14] Wang Y, Piao Y, Sun R C. Depth image super-resolution construction combined with high-resolution color image of the same scene[J]. Acta Optica Sinica, 37, 0810002(2017).

[15] Freeman W T, Jones T R, Pasztor E C. Example-based super-resolution[J]. IEEE Computer Graphics and Applications, 22, 56-65(2002).

[16] Chang H, Yeung D Y, Xiong Y. Super-resolution through neighbor embedding[C]. IEEE Conference on Computer Vision and Pattern Recognition, 1, 275-282(2004).

[17] Yang J, Wright J, Huang T et al. Image super-resolution via sparse representation[J]. IEEE Transactions on Image Processing, 19, 2861-2873(2010). http://europepmc.org/abstract/MED/20483687

[18] Xiao J S, Liu E Y, Zhu L et al. Improved image super-resolution algorithm based on convolutional neural network[J]. Acta Optica Sinica, 37, 0318002(2017).

[19] Zheng X T, Yuan Y, Lu X Q. Single image super-resolution restoration algorithm from external examples to internal self-similarity[J]. Acta Optica Sinica, 37, 0318004(2017).

[20] Zhou M, Chen H, Paisley J et al. Non-parametric Bayesian dictionary learning for sparse image representations[C]. International Conference on Neural Information Processing Systems, 21, 2295-2303(2009).

[21] Rodriguez A, Dunson D B. Nonparametric Bayesian models through probit stick-breaking processes[J]. Bayesian Analysis, 6, 145-177(2011). http://europepmc.org/abstract/med/24358072

[22] Knowles D, Ghahramani Z. Infinite sparse factor analysis and infinite independent components analysis[J]. Independent Component Analysis and Signal Separation, 4666, 381-388(2007).

[23] Paisley J, Carin L. Nonparametric factor analysis with beta process priors[C]. International Conference on Machine Learning, 777-784(2009).

[24] Zhou M, Yang H, Sapiro G et al. Dependent hierarchical beta process for image interpolation and denoising[C]. Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 15, 883-891(2011).

[25] Griffiths T L, Ghahramani Z. The Indian buffet process: an introduction and review[J]. Journal of Machine Learning Research, 12, 1185-1224(2011). http://www.ams.org/mathscinet-getitem?mr=2804598

[26] Bishop C. Pattern recognition and machine learning[M]. New York: Springer, 523-556(2006).

[27] Liu S, Zhu Y J, Xue L. Remote sensing image super-resolution method using sparse representation and classified texture patches[J]. Geomatics and Information Science of Wuhan University, 40, 578-582(2015).