[1] [1] SU Heng，ZHOU Jie，ZHANG Zhihao. Survey of Super-resolution Image Reconstruction Methods [J]. Acta Automatica Sinica，2013，39(8)：1202-1213.

[2] [2] Freeman T，Jones T R，Pasztor E C. Example based superresolution [J]. IEEE Computer Graphics and Applications (S0272-1716)，2002，22(2)：56-65.

[3] [3] YANG Chih-Yuan，LIU Sifei，YANG Ming-Hsuan. Structured Face Hallucination [C]// IEEE Conference on Computer Vision and Pattern Recognition (CVPR)，Portland，Oregon，USA，June 25-27，2013：1099-1106.

[4] [4] ZHAN Shu，WANG Jun，YANG Fumeng，et al. Gaussian Mixture Sparse Representation for Image Recognition Based on Gabor Features and Dictionary Learning [J]. Acta Electronica Sinica，2015，43(3)：523-528.

[5] [5] Elad M，Aharon M. Image denoising via sparse and redundant representations over learned dictionaries [J]. IEEE Transactions on Image Processing(S1063-6919)，2006，15(12)：3736-3745.

[6] [6] YANG Jianchao，Wright J，Thomas H，et al. Image super-resolution via sparse representation [J]. IEEE Transactions on Image Processing(S1057-7149)，2010，19(11)：2861-2873.

[7] [7] Zeyde R，Elad M，Protter M. On Single Image Scale-up using Sparse Representations [C]// Proceedings of the 7th International Conference on Curves and Surfaces，Avignon，France，June 24-30，2012，6920：711-730.

[8] [8] WANG Shenlong，ZHANG Lei，LIANG Yan，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(CVPR)， Providence，RI，USA，June 16-21，2012：2216-2223.

[9] [9] HE Li，QI Hairong，Zaretzki R. Beta Process Joint Dictionary Learning for Coupled Feature Spaces with Application to Single Image Super-Resolution [C]// IEEE Conference on Computer Vision and Pattern Recognition(CVPR)，Portland，Oregon， USA，June 25-27，2013：345-352.

[10] [10] Peleg T，Elad M. A statistical prediction model based on sparse representations for single image super-resolution [J]. IEEE Transactions on Image Processing(S1057-7149)，2014，23(6)：2569-2582.

[11] [11] PatiY C，Rezaiifar R，Krishnaprasad P S. Orthogonal matching pursuit：recursive function approximation with applications to wavelet decomposition [C]// Proceedings of the 27th Asilomar Conference on Signals，Systems and Computers. Pacific Grove，USA：Institute of Electrical and Electronics Engineers，1993：40-44.

[12] [12] CHEN Shaobing，Donoho D，Saunders M. Atomic decomposition by basis pursuit [J]. SIAM Review(S0036-1445)，2001， 43(1)：129-159.

[13] [13] DONG Weisheng，ZHANG Lei，SHI Guangming，et al. Image Deblurring and Super-Resolution by Adaptive Sparse Domain Selection and Adaptive Regularization [J]. IEEE Transactions on Image Processing(S1057-7149)，2011，20(7)：1838-1857.

[14] [14] PAN Zongxu，YU Jing，XIAO Chuangbai，et al. Single Image Super Resolution Based on Adaptive Multi-Dictionary Learning [J]. Acta Electronica Sinica，2015，43(2)：209-216.

[15] [15] Smith L N，Elad M. Improving Dictionary Learning：Multiple Dictionary Updates and Coefficient Reuse [J]. Signal Processing Letters(S1070-9908)，2013，20(1)：79-82.

[16] [16] CHEN Shuzhen，WEI Yanxin. Image Super-resolution Reconstruction Algorithms Based on Self-similarities and Dictionary Learning [J]. Opto-Electronic Engineering，2013，40(6)：106-113.

[17] [17] SHI Dawei，FU Randi，JIN Wei. A Method of Infrared Nephogram Super-resolutionBased on Coupled Over-completed sDictionary [J]. Opto-Electronic Engineering，2014，41(4)：69-74.