Hyperspectral Remote Sensing Image Processing and Information Extraction Technology Research in Geological Recognition Application

Abstract

Application of hyperspectral remote sensing technology in geological identification has highlighted its advantages, but the identification accuracy of metal mineral cations is limited. In this paper, the dominant spectrum of domestic HJ-1A data and Hyperion data are used for collaborative processing, realize multi-source hyperspectral image fusion and information extraction and recognition, mapping of mineral alteration information in the Qinghai-Tibet Plateau. The adopted method improves the identification accuracy of metal mineral cations in the visible light and near-infrared range. After comparative verification analysis and statistical evaluation of results, it is confirmed that this method has important application value for the identification of metal mineral cations in complex geological environment.