This work was funded by the National Natural Science Foundation Project of China (Grant No. 32271879), the Science and Technology Innovation Platform and Talent Plan Project of Hunan Province (Grant No. 2017TP1022), the National Natural Science Foundation of China Youth Project (Grant No. 32201552) and Changsha City Natural Science Foundation (Grant No. kq2202274).
机构署名：
本校为第一且通讯机构
院系归属：
林学院
摘要：
Aimed at addressing deficiencies in existing image fusion methods, this paper proposed a multi-level and multi-classification generative adversarial network (GAN)-based method (MMGAN) for fusing visible and infrared images of forest fire scenes (the surroundings of firefighters), which solves the problem that GANs tend to ignore visible contrast ratio information and detailed infrared texture information. The study was based on real-time visible and infrared image data acquired by visible and infrared binocular cameras on forest firefighters’ ...
