Aiming at the problem of inaccurate extraction of feature points of unevenly illuminated images and poor matching effect by traditional feature matching algorithms, this paper proposes an AKAZE image matching algorithm combined with single-parameter homomorphic filtering. The algorithm first compensates for the illumination information of the image through single-parameter homomorphic filtering; secondly, it uses the AKAZE algorithm to extract feature points of the image after the single-parameter homomorphic filtering, and then uses Hamming distance as the similarity measure to perform brute force matching on the feature points; Finally, the RANSAC algorithm based on the homography matrix is used for precise matching, and the wrong matching point pairs are eliminated. The experimental results show that the algorithm can not only effectively improve the brightness and contrast of the image, detect more feature points, but also improve the accuracy of matching, which has strong applicability.
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