Image cascade matching method based on an improved random sampling consistency algorithm

Abstract

In the process of image matching, image quality will have a certain impact on the extraction of image features, directly affecting the matching accuracy of subsequent images. Therefore, an image cascade matching method based on improved random sampling consistency algorithm is proposed. This method first needs to improve the quality of the matched target image through preprocessing results such as image denoising and enhancement, and prepare for feature point extraction during subsequent image cascade matching; Then extract the feature points of the target to be matched in the image, and use the improved random sampling consistency method to quickly estimate and simplify the registration model based on the extraction results. Use similar feature triangles to perform model pre testing, and use the maximum Euclidean distance method to improve the accuracy of image cascade registration, achieving image cascade matching. The experimental results show that the proposed method can achieve image enhancement while removing image noise, improve the quality of the image, comprehensively extract the feature points to be matched in the image, and achieve accurate matching of image feature points.