19 February 2008 A new similarity function for region based image fusion incorporating Gabor filters and fuzzy c-means clustering
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Proceedings Volume 6625, International Symposium on Photoelectronic Detection and Imaging 2007: Related Technologies and Applications; 66250Z (2008) https://doi.org/10.1117/12.791022
Event: International Symposium on Photoelectronic Detection and Imaging: Technology and Applications 2007, 2007, Beijing, China
Abstract
A new similarity function for region based image fusion is proposed incorporating with Gabor filters and FCM clustering in this paper. First, the fuzzy c-means clustering algorithm (FCM) is used to segment the image in the feature space formed by multi-channel Gabor filters. Second, wavelet decomposition is performed on the source images, and then the weighting factors are constructed based on the local energy and the new similarity function defined by Gabor filters. Finally, the fused image is obtained by taking inverse wavelet transform. The performance of the image fusion method is evaluated using five criteria including root mean square error, peek-to-peek signal-to-noise ratio, entropy, cross entropy and mutual information. The evaluation results indicate that the proposed image fusion method is effective.
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Xiao-Jun Wu, Xiao-Jun Wu, Dong-Xue Su, Dong-Xue Su, Xiao-Qing Luo, Xiao-Qing Luo, Shi-Tong Wang, Shi-Tong Wang, Jing-Yu Yang, Jing-Yu Yang, } "A new similarity function for region based image fusion incorporating Gabor filters and fuzzy c-means clustering", Proc. SPIE 6625, International Symposium on Photoelectronic Detection and Imaging 2007: Related Technologies and Applications, 66250Z (19 February 2008); doi: 10.1117/12.791022; https://doi.org/10.1117/12.791022
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