Fast filtering image fusion

JEI 2017: Fast filtering image fusion

Image fusion aims at exploiting complementary information in multi-modal images to create a single composite image with extended information content. In this paper, an image fusion framework is proposed for different types of multi-modal images with fast filtering in the spatial domain. Firstly, image gradient magnitude is used to detect contrast and image sharpness. Secondly, a fast morphological closing operation is performed on image gradient magnitude to bridge gaps and full holes. Thirdly, the weight map is obtained from the multi-modal 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.
If you use these codes, please cite the paper:
@Article{ZhanJEI2017october,
author = {Zhan, Kun and Xie, Yuange and Wang, Haibo and Min, Yufang},
title = {Fast filtering image fusion},
journal = {Journal of Electronic Imaging},
year = {2017},
volume = {26},
number = {nn},
pages = {pp},
}

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