A Remote Sensing Image Subpixel Matching Combined Genetic Algorithm with Least Square Matching
Renxiang Wang · 2001
Image matching is a very important task in either computer vision or digital photogrammetry. In the paper, an approach to remote sensing image matching combining genetic algorithm(GA) with least square matching(LSM) is presented to speed up image matching and provide a robust reliable and relatively accurate initial value for high-precision subpixel matching. The experiment shows that the matching method based on GA is much faster than those based on Sequential Similarity Detection Algorithm(SSDA) and classical Mean Absolute Difference(MAD). Taking our experiment data as an example, the rate of the sum of correlation calculation of MAD to that of GA is at least 36∶1. This fact is proved theoretically.