Infrared and visible light image fusion method based on GAN and attention mechanism
In order to improve the ability of generative adversarial network fusion methods to extract information from infrared and visible light images,a new visible and infrared image fusion method based on generative adversarial network is proposed.In the generator model,dual channels are used to extract features from infrared and visible light images,and attention mechanism is intro-duced to enhance the dependency relationship between each pixel,Enable the fusion of images to better preserve information from in-frared and visible light images.And Markov discriminator(PatchGAN)is used as the discriminator for the fusion framework in this pa-per.The experimental results show that compared to existing image fusion methods,the fused images obtained by this method have rich-er texture details,higher contrast,better visual effects,and have varying degrees of improvement in objective evaluation indicators such as similarity,correlation coefficient,and peak signal-to-noise ratio.