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Proceedings Paper

A new similarity function for region based image fusion incorporating Gabor filters and fuzzy c-means clustering
Author(s): Xiao-Jun Wu; Dong-Xue Su; Xiao-Qing Luo; Shi-Tong Wang; Jing-Yu Yang
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Paper 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.

Paper Details

Date Published: 19 February 2008
PDF: 10 pages
Proc. SPIE 6625, International Symposium on Photoelectronic Detection and Imaging 2007: Related Technologies and Applications, 66250Z (19 February 2008); doi: 10.1117/12.791022
Show Author Affiliations
Xiao-Jun Wu, Jiangnan Univ. (China)
Dong-Xue Su, Jiangsu Univ. of Science and Technology (China)
Xiao-Qing Luo, Jiangnan Univ. (China)
Shi-Tong Wang, Jiangnan Univ. (China)
Jing-Yu Yang, Nanjing Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 6625:
International Symposium on Photoelectronic Detection and Imaging 2007: Related Technologies and Applications

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