[1] [1] TANG L F, YUAN J, MA J Y. Image fusion in the loop of high-level vision tasks: a semantic-aware real-time infrared and visible image fusion network[J]. Information Fusion, 2022, 82: 28-42.

[3] [3] ZHANG X. Deep learning-based multi-focus image fusion: a survey and a comparative study[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021, 44(9): 4819-4838.

[4] [4] MA Jiayi, ZHOU Yi. Infrared and visible image fusion via gradientlet filter[J]. Computer Vision and Image Understanding, 2020(197-198): 103016.

[5] [5] LI G, LIN Y, QU X. An infrared and visible image fusion method based on multi-scale transformation and norm optimization[J]. Information Fusion, 2021, 71: 109-129.

[6] [6] MA J Y, YU W, LIANG P W, et al. FusionGAN: a generative adversarial network for infrared and visible image fusion[J]. Information Fusion, 2019, 48: 11-26.

[8] [8] TANG L F, YUAN J, MA J Y，et al. PIAFusion: a progressive infrared and visible image fusion network based on illumination aware[J]. Information Fusion, 2022, 83: 79-92.

[9] [9] TANG L F, XIANG X Y, ZHANG H, et al. DIVFusion: darkness-free infrared and visible image fusion[J]. Information Fusion, 2023, 91: 477-493.

[10] [10] YU F, JUN X W, Tariq D. Image fusion based on generative adversarial network consistent with perception[J]. Information Fusion, 2021, 72: 110-125.

[12] [12] ZHANG Y, LIU Y, SUN P, et al. IFCNN: a general image fusion framework based on convolutional neural network[J]. Information Fusion, 2020, 54: 99-118.

[13] [13] MA J Y, XU H, JIANG J, et al. DDcGAN: a dual-discriminator conditional generative adversarial network for multi-resolution image fusion[J]. IEEE Transactions on Image Processing, 2020, 29: 4980-4995.

[14] [14] MA J, ZHANG H, SHAO Z, et al. GANMcC: a generative adversarial network with multiclassification constraints for infrared and visible image fusion[J]. IEEE Transactions on Instrumentation and Measurement, 2021, 70: 1-14.

[15] [15] Prabhakar K R, Srikar V S, Babu R V. DeepFuse: a deep unsupervised approach for exposure fusion with extreme exposure image pairs[C]//IEEE International Conference on Computer Vision (ICCV), 2017: 4724-4732.