Abstract
SAR and visible image matching provides many applications in remote sensing, image fusion and image guidance with laborious problems with regard to the potential nonlinear intensity differences between two images. This paper proposes an image matching approach which use the phase congruency (PC) to detect corners and log-gabor filters for obtaining feature descriptor in the SAR and visible images. PC can provide inherent and rich image textures for the images with intricate grayscale changes or noise, which is utilitized to detect the corners. The moments of PCs for the images are calculated to obtain the keypoints and the log-gabor filters are employed to acquire the feature descriptors. Five evaluation methods are used for testing the results of the algorithm for three pairs of images and its result is compared to the SIFT algorithm. The experiment performance show that the advocated algorithm is better than the SIFT algorithm.
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Acknowledgments
Heilongjiang Provincial Natural Science Foundation of China under Grant No. QC2015072, and Jiamusi University Young Innovative Talents Training Program No. 22Zq201506, Heilongjiang Prvincial Innovative Training Program for College Students No. 201610222066, Doctoral Program of Jiamusi University No. 22Zb201519, Excellent discipline team project of Jiamusi University (No. JDXKTD-2019008).
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Liu, X., Zhao, H., Ma, H., Li, J. (2020). Image Matching Using Phase Congruency and Log-Gabor Filters in the SAR Images and Visible Images. In: Pan, JS., Lin, JW., Liang, Y., Chu, SC. (eds) Genetic and Evolutionary Computing. ICGEC 2019. Advances in Intelligent Systems and Computing, vol 1107. Springer, Singapore. https://doi.org/10.1007/978-981-15-3308-2_31
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DOI: https://doi.org/10.1007/978-981-15-3308-2_31
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