文献类型：期刊文献

英文题名：Multi-Source Pansharpening of Island Sea Areas Based on Hybrid-Scale Regression Optimization

作者：Fu, Dongyang[1,2];Ma, Jin[1,2];Liu, Bei[1,2];Zhu, Yan[1]

机构：[1]Guangdong Ocean Univ, Sch Elect & Informat Engn, Zhanjiang 524088, Peoples R China;[2]Guangdong Prov Marine Remote Sensing & Informat Te, Zhanjiang 524088, Peoples R China

年份：2025

卷号：25

期号：11

外文期刊名：SENSORS

收录：SCI-EXPANDED(收录号：WOS:001506135100001)、、EI(收录号：20252418594273)、Scopus(收录号：2-s2.0-105007670485)、WOS

基金：This work is supported by the National Key Research and Development Program of China under grant 2022YFC3103101, the Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (GML2021GD0809), the National Natural Science Foundation of China (No. 42206187), Key projects of the Guangdong Education Department (2023ZDZX4009).

语种：英文

外文关键词：pansharpening; sentinel remote sensing imagery; mixed-scale regression; mutual information; South Sea Islands

外文摘要：To address the demand for high spatial resolution data in the water color inversion task of multispectral satellite images in island sea areas, a feasible solution is to process through multi-source remote sensing data fusion methods. However, the inherent biases among multi-source sensors and the spectral distortion caused by the dynamic changes of water bodies in island sea areas restrict the fusion accuracy, necessitating more precise fusion solutions. Therefore, this paper proposes a pansharpening method based on Hybrid-Scale Mutual Information (HSMI). This method effectively enhances the accuracy and consistency of panchromatic sharpening results by integrating mixed-scale information into scale regression. Secondly, it introduces mutual information to quantify the spatial-spectral correlation among multi-source data to balance the fusion representation under mixed scales. Finally, the performance of various popular pansharpening methods was compared and analyzed using the coupled datasets of Sentinel-2 and Sentinel-3 in typical island and reef waters of the South China Sea. The results show that HSMI can enhance the spatial details and edge clarity of islands while better preserving the spectral characteristics of the surrounding sea areas.