Infrared and Visible Image Fusion Method Based on Dual-path Cascade Adversarial Mechanism

Lili TANG; Gang LIU; Gang XIAO

doi:10.3788/gzxb20215009.0910004

[1] Zhongliang JING, Gang XIAO, Zhenhua LI. Image fusion： theory and applications, 3-5(2007).

[2] Zhiqiang ZHOU, Bo WANG, Sun LI et al. Perceptual fusion of infrared and visible images through a hybrid multi-scale decomposition with Gaussian and bilateral filters. Information Fusion, 30, 15-26(2016).

[3] Xingchen ZHANG, Ping YE, Shenyun PENG et al. SiamFT： an RGB-infrared fusion tracking method via fully convolutional siamese networks. IEEE Access, 7, 122122-122133(2019).

[4] H TORRESAN, D D BURLEIGH, K E CRAMER et al. Advanced surveillance systems： combining video and thermal imagery for pedestrian detection, 5405, 506-515(2004).

[5] Jiao DU, Weisheng LI, Ke LU et al. An overview of multi-modal medical image fusion. Neurocomputing, 215, 3-20(2016).

[6] Shutao LI, Xudong KANG, Leyuan FANG et al. Pixel-level image fusion： a survey of the state of the art. Information Fusion, 33, 100-112(2017).

[7] Xiaoqi LU, Baohua ZHANG, Ying ZHAO et al. The infrared and visible image fusion algorithm based on target separation and sparse representation. Infrared Physics & Technology, 67, 397-407(2014).

[8] Shutao LI, Xudong KANG, Jianwen HU. Image fusion with guided filtering. IEEE Transactions on Image Processing, 22, 2864-2875(2013).

[9] Yu LIU, Xun CHEN, Hu PENG et al. Multi-focus image fusion with a deep convolutional neural network. Information Fusion, 36, 191-207(2017).

[10] Qilei LI, Lu LU, Zhen LI et al. Coupled GAN with relativistic discriminators for infrared and visible images fusion. IEEE Sensors Journal, 21, 7458-7567(2019).

[11] Jiayi MA, Wei YU, Pingwei LIANG et al. FusionGAN： a generative adversarial network for infrared and visible image fusion. Information Fusion, 48, 11-26(2019).

[12] I GOODFELLOW, J POUGET-ABADIE, M MIRZA, 2672-2680(2014).

[13] Huang GAO, Zhuang LIU, V D M LAURENS et al. Densely connected convolutional networks, 4700-4708(2017).

[14] A RADFORD, L METZ, S CHINTALA. Unsupervised representation learning with deep convolutional generative adversarial networks. arXiv：(1511).

[15] Jiayi MA, Chen CHEN, Chang LI et al. Infrared and visible image fusion via gradient transfer and total variation minimization. Information Fusion, 31, 100-109(2016).

[16] Dongdong XU, Yongcheng WANG, shuyan XU et al. Infrared and visible image fusion with a generative adversarial network and a residual network. Applied Sciences, 10, 554(2020).

[17] TNO image fusion dataset(2018). 15

[18] Xingchen ZHANG, Ping YE, Gang XIAO. VIFB： a visible and infrared image fusion benchmark, 2020, 468-478.

[19] S KUMAR. Image fusion based on pixel signifificance using cross bilateral filter. Signal, 9, 1193-1204(2015).

[20] Yu LIU, Xun CHEN, R K WARD et al. Image fusion with convolutional sparse representation. IEEE Signal Processing Letters, 23, 1882-1886(2016).

[21] Xueqin GAO, Gang LIU, Gang XIAO等. Fusion algorithm of infrared and visible images based on FPDE. Journal of Automation, 46, 796-804(2020).

[22] Hui LI, Xiaojun WU. DenseFuse： A fusion approach to infrared and visible images. IEEE Transactions on Image Processing, 28, 2614-2623(2018).

[23] Jiayi MA, Han XU, Junjun JIANG et al. DDcGAN： a dual-discriminator conditional generative adversarial network for multi-resolution image fusion. IEEE Transactions on Image Processing, 29, 4980-4995(2020).

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

[25] Jiayi MA, Yong MA, Chang LI. Infrared and visible image fusion methods and applications：a survey. Information Fusion, 45, 153-178(2019).