[1] MA J, MA Y, LI C. Infrared and visible image fusion methods and applications: A survey[J]. Information Fusion, 2019, 45: 153-178.
[2] LI S, KANG X, FANG L, et al. Pixel-level image fusion: a survey of the state of the art[J]. Information Fusion, 2017, 33: 100-112.
[3] Elguebaly T, Bouguila N. Finite asymmetric generalized Gaussian mixture models learning for infrared object detection[J]. Computer Vision and Image Understanding, 2013, 117(12): 1659-1671.
[4] LI H, DING W, CAO X, et al. Image registration and fusion of visible and infrared integrated camera for medium-altitude unmanned aerial vehicle remote sensing[J]. Remote Sensing, 2017, 9(5): 441.
[5] LI S, YANG B, HU J. Performance comparison of different multi-resolution transforms for image fusion[J]. Information Fusion, 2011, 12(2): 74-84.
[6] FU Z, WANG X, XU J, et al. Infrared and visible images fusion based on RPCA and NSCT[J]. Infrared Physical Technology, 2016, 77: 114-123.
[7] ZHANG Q, LIU Y, Blum R, et al. Sparse representation based multi-sensor image fusion for multi-focus and multi-modality images: a review[J]. Information Fusion, 2018, 40: 57-75.
[8] ZHANG Z, XU Y, YANG J, et al. A survey of sparse representation: Algorithms and Applications[J]. IEEE Access, 2015(3): 490-530.
[9] YANG B, LI S. Multifocus image fusion and restoration with sparse representation[J]. IEEE Transactions on Instrumentation and Measurement, 2010, 59(4): 884-892.
[10] YU N, QIU T, BI F, et al. Image features extraction and fusion based on joint sparse representation[J]. IEEE Journal of Selected Topics in Signal Processing, 2011, 5(5): 1074-1082.
[11] LIU Y, WANG Z. Simultaneous image fusion and denoising with adaptive sparse representation[J]. IET Image Processing, 2014, 9(5): 347-357.
[12] LIU Y, LIU S, WANG Z. A general framework for image fusion based on multi-scale transform and sparse representation[J]. Information Fusion, 2015, 24: 147-164.
[13] WANG Z, YANG F, PENG Z, et al. Multi-sensor image enhanced fusion algorithm based on NSST and top-hat transformation[J]. Optik, 2015, 126(23): 4184-4190.
[14] WANG Z, XU J, JIANG X, et al. Infrared and visible image fusion via hybrid decomposition of NSCT and morphological sequential toggle operator[J]. Optik, 2020, 201: 163497.
[16] LI H, WU X J. DenseFuse: A Fusion Approach to Infrared and Visible Images[J]. IEEE Transaction Image Processing, 2019, 28(5): 2614- 2623.
[17] MA J, YU W, LIANG P, et al. Fusion GAN: A generative adversarial network for infrared and visible image fusion[J]. Information Fusion, 2019, 48: 11-26.
[20] ZHANG J, ZHAO D, GAO W. Group-based sparse representation for image restoration[J]. IEEE Transactions on Image Processing, 2014, 23(8): 3336-3351.
[21] WANG Z, Bovik A, A universal image quality index[J]. IEEE Signal Processing Letters. 2002, 9(3): 81–84.
[22] Piella G, Heijmans H. A new quality metric for image fusion[C]// Proceedings of the 10th International Conference on Image Processing, 2003: 173-176.
[23] Xydeas C.S, Petrovic V, Objective image fusion performance measure[J]. Electronics Letters, 2000, 36(4): 308-309.