[1] Juefei-Xu F, Savvides M. Single face image super-resolution via solo dictionary learning[C]//IEEE International Conference on Image Processing (ICIP), 2015:2239-2243.
[2] Tang Yi, Wan Jianwei, Nian Yongjian. Distributed near lossless compression of hyperspectral images[J]. Acta Optica Sinica, 2015, 35(3):0310001.
[3] Wang Yiqun, Yan Changxiang, Miao Chun'an. Choice of spectral-splitting modes in space-borne hyperspectral imager[J]. Chinese Journal of Optics and Applied Optics, 2009, 2(4):304-308. (in Chinese)
[4] Xiao J, Pang G, Zhang Y, et al. Adaptive shock filter for image super-resolution and enhancement[J]. Journal of Visual Communication and Image Representation, 2016, 40:168-177.
[5] Zhang K, Tao D, Gao X, et al. Learning multiple linear mappings for efficient single image super-resolution[J]. IEEE Transactions on Image Processing, 2015, 24(3):846-861.
[6] Harris J L. Diffraction and resolving power[J]. Journal of the Optical Society of America, 1964, 54(7):931-936.
[7] Goodman J W. Introduction to Fourier Optics[M]. New York:Mc Graw-Hill, 1968.
[8] Batz M, Eichenseer A, Selier J, et al. Hybrid super-resolution combining example-based single-image and interpolation-based multi-image reconstruction approaches[C]//2015 IEEE International Conference on Image Processing (ICIP), 2015:58-62.
[9] Zhou Jinghong, Zhou Cui, Zhu Jianjun, et al. A method of super-resolution reconstruction for remote sensing image based on non-subsampled contourlet transform[J]. Acta Optica Sinica, 2015, 35(1):0110001. (in Chinese)
[10] Lian Qiusheng, Zhang Wei. Image super-resolution algorithms based on sparse representation of classified image patches[J]. Acta Electronica Sinica, 2012, 40(5):920-925. (in Chinese)
[11] Zhao Y Q, Yang J X, Zhang Q Y, et al. Hyperspectral imagery super-resolution by sparse representation and spectral regularization[J]. EURASIP Journal on Advances in Signal Processing, 2011, 2011(1):87.
[12] Pan Zongxu, Yu Jing, Xiao Chuangbai, et al. Spectral similarity-based super resolution for hyperspectral images[J].Acta Automatica Sinica, 2014, 40(12):2797-2807. (in Chinese)
[13] Fu Fazuo. Hyperspectral image super-resolution based on non-negative dictionary learning[D]. Xi'an:Xidian University, 2018. (in Chinese)
[14] Tropp J A, Wright S J. Computational methods for sparse solution of linear inverse problems[J]. Proceedings of the IEEE, 2010, 98(6):948-958.
[15] Boyd S, Van den berghe L. Convex Optimization[M]. Cambridge:Cambridge University Press, 2009:291-293.
[16] Yang M, Zhang L, Yang J, et al. Robust sparse coding for face recognition[C]//IEEE Conference on Computer Vision and Pattern Recognition(CVPR), 2011:625-632.
[17] Xu Guoming, Xue Mogen, Yuan Guangling. Image super-resolution reconstruction method via mixture gaussian sparse coding[J]. Opto-Electronic Engineering, 2013, 40(3):94-101. (in Chinese)
[18] Yang J C, Wright J, Huang T, et al. Image super-resolution via sparse representation[J]. IEEE Transactions on Image Processing, 2010, 19(11):2861-2873.
[19] Saad M A, Bovik A C, Charrier C. Model-based blind image quality assessment:a natural scene statistics approach in the DCT domain[J]. IEEE Transactions on Image Processing, 2012, 21(8):3339-9952.
[20] Akgun T, Altunbasak Y, Mersereau R M. Super-resolution reconstruction of hyperspectral images[J]. IEEE Transactions on Image Processing, 2005, 14(11):1860-1875.