Deep blind super-resolution for hyperspectral images

Pei Yang, Yong Ma, Xiaoguang Mei, Qihai Chen, Minghui Wu, Jiayi Ma

Abstract: Highlights•A novel blind super-resolution algorithm for the single hyperspectral image is proposed for the first time, effectively addressing the issue of unknown degradation in hyperspectral images.•We propose a blur kernel estimation module and a deblurring module to obtain the clean hyperspectral image without blur.•We design the branch and fusion module to exploit the spatial-spectral information from both the local and global perspectives to further remove degradation.•Experimental results validate that the proposed method has superior performance and better generalization capability.