文章基本信息

标题：A remote sensing image matching method combining genetic algorithms with least square matching
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作者：Xing Hua Xiong
期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2000
卷号：XXXIII Part B3(/1+2)
页码：67-73
出版社：Copernicus Publications
摘要：Image matching is an important task in digital photogrammetry. In the paper, an approach to remote sensing imagematching combining genetic algorithm(GA) with least square matching(LSM) is presented to speed up image matchingand provide a robust reliable and rather accurate initial value for high-precision subpixel matching. The experimentshow that the matching method based on GA is much faster than those based on Sequential Similarity DetectionAlgorithm(SSDA) and classical Mean Absolute Difference(MAD). Taking our experiment data as an example, the rateof the sum of correlation calculation of MAD to that of GA is at least 34:1, this is to say, the speed of the later is thirtyfourtimes faster than that of the former theoretically
关键词：Remote Sensing; Image Matching; Genetic Algorithm; Least Square Matching