[1] Park S C, Park M K, Kang M G. Super-resolution image reconstruction: a technical overview[J]. IEEE Signal Processing Magazine, 2003, 20(3): 21–36.

[2] Zhan S, Fang Q. Image super-resolution based on edge-enhancement and multi-dictionary learning[J]. Opto-Electronic Engineering, 2016, 43(4): 40–47.

[3] Su H, Zhou J, Zhang Z H. Survey of super-resolution image reconstruction methods[J]. Acta Automatica Sinica, 2013, 39(8): 1202–1213.

[4] Tsai R Y. Multiframe image restoration and registration[J]. Advances in Computer Vision and Image Processing, 1984, 1(2): 317–339.

[5] Wu C Z, Hu C S, Zhang M J, et al. Single image super- resolution reconstruction via supervised multi-dictionary learning[J]. Opto-Electronic Engineering, 2016, 43(11): 69–75.

[6] Wang R G, Wang Q H, Yang J, et al. Image super-resolution reconstruction by fusing feature classification and independent dictionary training[J]. Opto-Electronic Engineering, 2018, 45(1): 170542.

[7] Freeman W T, Jones T R, Pasztor E C. Example-based super- resolution[J]. IEEE Computer Graphics and Applications, 2002, 22(2): 56–65.

[8] Chang H, Yeung D Y, Xiong Y M. Super-resolution through neighbor embedding[C]//Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004: I.

[9] Roweis S T, Saul L K. Nonlinear dimensionality reduction by locally linear embedding[J]. Science, 2000, 290(5500): 2323–2326.

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

[11] Zeyde R, Elad M, Protter M. On single image scale-up using sparse-representations[C]//International Conference on Curves and Surfaces, Berlin, Heidelberg, 2010, 6920: 711–730.

[12] Aharon M, Elad M, Bruckstein A. rmK-SVD: An algorithm for designing overcomplete dictionaries for sparse representation[ J]. IEEE Transactions on Signal Processing, 2006, 54(11): 4311–4322.

[13] Yang C Y, Yang M H. Fast direct super-resolution by simple functions[C]//Proceedings of 2013 IEEE International Conference on Computer Vision, 2013: 561–568.

[14] Zhang L, Yang M, Feng X C. Sparse representation or collaborative representation: Which helps face recognition[C]// Proceedings of 2011 IEEE International Conference on Computer Vision, 2011: 471–478.

[15] Timofte R, De Smet V, Van Gool L. Anchored neighborhood regression for fast example-based super-resolution[C]// Proceedings of 2013 IEEE International Conference on Computer Vision, 2013: 1920–1927.

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

[17] Bevilacqua M, Roumy A, Guillemot C, et al. Low-complexity single-image super-resolution based on nonnegative neighbor embedding[C]// Proceedings British Machine Vision Conference, 2012: 135.