Extraction and Fusion of Geographic Information from Multi-source Remote Sensing Images Based on Artificial Intelligence

Abstract

Multi-source RS image fusion technology is mainly a data processing technology to organize and correlate the image data of the same scene under different imaging modes through specific calculation rules, and then obtain more accurate, perfect and rich information of comprehensive images. The information contained in remote sensing (RS) images of different sensors is imprecise, uncertain and fuzzy to varying degrees, so the fusion method used in fusing these information must solve these problems. The way to solve the problem of image registration is to solve the problem of relative correction of images. On the basis of analyzing and discussing the principle, hierarchy, structure and characteristics of multi-source RS image data fusion, this article puts forward the extraction and fusion technology of multi-source RS image geographic information combined with artificial intelligence (AI) algorithm. Compared with K-means classification method, this classification fusion method can effectively reduce the uncertain information in the classification process and improve the classification accuracy. The results verify the feasibility of the extraction and fusion method of geographic information from multi-source RS images proposed in this article in practical application.