7 November 2017 Fast filtering image fusion
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Abstract
Image fusion aims at exploiting complementary information in multimodal images to create a single composite image with extended information content. An image fusion framework is proposed for different types of multimodal images with fast filtering in the spatial domain. First, image gradient magnitude is used to detect contrast and image sharpness. Second, a fast morphological closing operation is performed on image gradient magnitude to bridge gaps and fill holes. Third, the weight map is obtained from the multimodal image gradient magnitude and is filtered by a fast structure-preserving filter. Finally, the fused image is composed by using a weighed-sum rule. Experimental results on several groups of images show that the proposed fast fusion method has a better performance than the state-of-the-art methods, running up to four times faster than the fastest baseline algorithm.
© 2017 SPIE and IS&T
Kun Zhan, Kun Zhan, Yuange Xie, Yuange Xie, Haibo Wang, Haibo Wang, Yufang Min, Yufang Min, } "Fast filtering image fusion," Journal of Electronic Imaging 26(6), 063004 (7 November 2017). https://doi.org/10.1117/1.JEI.26.6.063004 . Submission: Received: 16 May 2017; Accepted: 17 October 2017
Received: 16 May 2017; Accepted: 17 October 2017; Published: 7 November 2017
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