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Remote Sensing Image Registration Based on SIFT and Mutual Information Screening Optimization |
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Abstract Aiming at the problem of a high mismatch rate in multi-source multi-scale image registration, an image registration algorithm based on SIFT and mutual information screening optimization was proposed. Firstly, the paper uses SIFT algorithm for feature point extraction, and uses FLANN algorithm to complete the rough matching of the image to be registered. Secondly, the background area is set up around the initial matching point, the regional mutual information value between matching points is calculated, and the matching point with small mutual information value is iteratively eliminated. Then, the homography transformation matrix between matching points after filtering optimization is solved, and the image registration is completed using perspective transformation. Finally, the post-registration image with the maximum mutual information value is output as the best registration result. Experimental results show that the algorithm can effectively improve the registration accuracy of multi-source and multi-scale remote sensing images.
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Received: 11 July 2020
Published: 15 November 2021
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