[1] [1] 1刘先红， 陈志斌， 秦梦泽. 结合引导滤波和卷积稀疏表示的红外与可见光图像融合［J］. 光学 精密工程， 2018， 26（5）： 1242-1253. doi: 10.3788/OPE.20182605.1242LIUX H， CHENZ B， QINM Z. Infrared and visible image fusion using guided filter and convolutional sparse representation［J］. Optics and Precision Engineering， 2018， 26（5）： 1242-1253.（in Chinese）. doi: 10.3788/OPE.20182605.1242

[2] LI H, WANG Q, WANG H et al. Infrared small target detection using tensor based least mean square[J]. Computers & Electrical Engineering, 91, 106994(2021).

[3] MA J Y, MA Y, LI C. Infrared and visible image fusion methods and applications： a survey[J]. Information Fusion, 45, 153-178(2019).

[4] DINH P H. Combining Gabor energy with equilibrium optimizer algorithm for multi-modality medical image fusion[J]. Biomedical Signal Processing and Control, 68, 102696(2021).

[5] LIU S, ZHAO H, DU Q et al. Novel cross-resolution feature-level fusion for joint classification of multispectral and panchromatic remote sensing images[J]. IEEE Transactions on Geoscience and Remote Sensing, 1-13(2021).

[6] LIU W, WANG Z F. A novel multi-focus image fusion method using multiscale shearing non-local guided averaging filter[J]. Signal Processing, 166, 107252(2020).

[7] ZHANG Q, LIU Y, BLUM R S et al. Sparse representation based multi-sensor image fusion for multi-focus and multi-modality images： a review[J]. Information Fusion, 40, 57-75(2018).

[8] [8] 8于国栋， 王春阳， 兰孝野， 等. 基于离线标定的快速图像拼接算法［J］. 液晶与显示， 2021， 36（10）： 1430-1436. doi: 10.37188/CJLCD.2020-0330YUG D， WANGC Y， LANX Y， et al. Fast image mosaic algorithm based on offline calibration［J］. Chinese Journal of Liquid Crystals and Displays， 2021， 36（10）： 1430-1436.（in Chinese）. doi: 10.37188/CJLCD.2020-0330

[9] LIU S H, TREMBLAIS B, CARRE P et al. Image reconstruction from multiscale singular points based on the dual-tree complex wavelet transform[J]. Security and Communication Networks, 2021, 6752486(2021).

[10] LI X S, ZHOU F Q, TAN H S et al. Multi-focus image fusion based on nonsubsampled contourlet transform and residual removal[J]. Signal Processing, 184, 108062(2021).

[11] [11] 11刘博， 韩广良， 罗惠元. 基于多尺度细节的孪生卷积神经网络图像融合算法［J］. 液晶与显示， 2021， 36（9）： 1283-1293. doi: 10.37188/CJLCD.2020-0339LIUB， HANG L， LUOH Y. Image fusion algorithm based on multi-scale detail Siamese convolutional neural network［J］. Chinese Journal of Liquid Crystals and Displays， 2021， 36（9）： 1283-1293.（in Chinese）. doi: 10.37188/CJLCD.2020-0339

[12] ZHENG Y J, LIU S C, DU Q et al. A novel multitemporal deep fusion network （MDFN） for short-term multitemporal HR images classification[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 10691-10704(2021).

[13] [13] 13杨艳春， 高晓宇， 党建武， 等. 基于WEMD和生成对抗网络重建的红外与可见光图像融合［J］. 光学 精密工程， 2022， 30（3）： 320-330. doi: 10.37188/OPE.20223003.0320YANGY C， GAOX Y， DANGJ W， et al. Infrared and visible image fusion based on WEMD and generative adversarial network reconstruction［J］. Optics and Precision Engineering， 2022， 30（3）： 320-330.（in Chinese）. doi: 10.37188/OPE.20223003.0320

[14] YAO T T, HU J C, ZHANG B et al. Scale and appearance variation enhanced Siamese network for thermal infrared target tracking[J]. Infrared Physics & Technology, 117, 103825(2021).

[15] LIU Y, CHEN X, PENG H et al. Multi-focus image fusion with a deep convolutional neural network[J]. Information Fusion, 36, 191-207(2017).

[16] MA J Y, YU W, LIANG P W et al. FusionGAN： a generative adversarial network for infrared and visible image fusion[J]. Information Fusion, 48, 11-26(2019).

[17] PRABHAKAR K R, SRIKAR V S, BABU R V. Deepfuse： A deep unsupervised approach for exposure fusion with extreme exposure image pairs[C], 4724-4732(2017).

[18] LI H, WU X J, DURRANI T S. Infrared and visible image fusion with ResNet and zero-phase component analysis[J]. Infrared Physics & Technology, 102, 103039(2019).

[19] AN W B, WANG H M. Infrared and visible image fusion with supervised convolutional neural network[J]. Optik, 219, 165120(2020).

[20] ZHU W Q, TANG X Y, ZHANG R et al. Infrared and visible image fusion based on edge-preserving and attention generative adversarial network[J]. Journal of Infrared and Millimeter Waves, 40, 696-708(2021).

[21] GUO X, MENG L Y, MEI L et al. Multi-focus image fusion with Siamese self-attention network[J]. IET Image Processing, 14, 1339-1346(2020).

[22] [22] 22张红颖， 安征. 基于改进双流时空网络的人体行为识别［J］. 光学 精密工程， 2021， 29（2）： 420-429. doi: 10.37188/OPE.20212902.0420ZHANGH Y， ANZ. Human action recognition based on improved two-stream spatiotemporal network［J］. Optics and Precision Engineering， 2021， 29（2）： 420-429.（in Chinese）. doi: 10.37188/OPE.20212902.0420

[23] WEI B Z, FENG X C, WANG K et al. The multi-focus-image-fusion method based on convolutional neural network and sparse representation[J]. Entropy （Basel， Switzerland）, 23, 827(2021).

[24] LI H, WU X J, KITTLER J. MDLatLRR： a novel decomposition method for infrared and visible image fusion[J]. IEEE Transactions on Image Processing, 29, 4733-4746(2020).

[25] GAO C, SONG C C, ZHANG Y C et al. Improving the performance of infrared and visible image fusion based on latent low-rank representation nested with rolling guided image filtering[J]. IEEE Access, 9, 91462-91475(2021).