PAPS: Progressive Attention-Based Pan-sharpening

作     者：Yanan Jia Qiming Hu Renwei Dian Jiayi Ma Xiaojie Guo Yanan Jia;Qiming Hu;Renwei Dian;Jiayi Ma;Xiaojie Guo

作者机构：College of Intelligence and ComputingTianjin UniversityTianjin 300350 China IEEE School of RoboticsHunan UniversityChangsha 410082China Electronic Information SchoolWuhan UniversityWuhan 430072China 

出 版 物：《IEEE/CAA Journal of Automatica Sinica》 (自动化学报（英文版）)

年 卷 期：2024年第11卷第2期

页      面：391-404页

核心收录：

学科分类：08[工学] 080203[工学-机械设计及理论] 0802[工学-机械工程] 

基　　金：partially supported by the National Natural Science Foundation of China (62372251) 

主　　题：High-resolution multispectral image image fusion pan-sharpening progressive enhancement 

摘      要：Pan-sharpening aims to seek high-resolution multispectral(HRMS) images from paired multispectral images of low resolution(LRMS) and panchromatic(PAN) images, the key to which is how to maximally integrate spatial and spectral information from PAN and LRMS images. Following the principle of gradual advance, this paper designs a novel network that contains two main logical functions, i.e., detail enhancement and progressive fusion, to solve the problem. More specifically, the detail enhancement module attempts to produce enhanced MS results with the same spatial sizes as corresponding PAN images, which are of higher quality than directly up-sampling LRMS *** a better MS base(enhanced MS) and its PAN, we progressively extract information from the PAN and enhanced MS images, expecting to capture pivotal and complementary information of the two modalities for the purpose of constructing the desired HRMS. Extensive experiments together with ablation studies on widely-used datasets are provided to verify the efficacy of our design, and demonstrate its superiority over other state-of-the-art methods both quantitatively and qualitatively. Our code has been released at https://***/JiaYN1/PAPS.