Open Access
22 September 2014 Adaptive multistrategy image fusion method
Xiao-qing Luo, Zhan-cheng Zhang, Xiao-jun Wu
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Abstract
Design of fusion rule is an important step in fusion process. Traditional single fusion rules are inflexible when they are being used to fuse feature-rich images. To address this problem, an adaptive multistrategy image fusion method is proposed. Its flexibility lies in the combination of a choose-max strategy and a weighted average strategy. Moreover, the region-based characteristics and the shift-invariant shearlet transform (SIST)-based activity measures are proposed to guide the selection of strategies. The key points of our method are: (1) Window-based features are extracted from the source images. (2) Use of the fuzzy c-means clustering algorithm to construct a region map in the feature difference space. (3) The dissimilarity between corresponding regions is employed to quantify the characteristic of regions and the local average variance of the SIST coefficients are considered as activity measures to evaluate the salience of the related coefficient. (4) The adaptive multistrategy selection scheme is achieved by a sigmoid function. Experimental results show that the proposed method is superior to the conventional image fusion methods both in subjective and objective evaluations.
© 2014 SPIE and IS&T 0091-3286/2014/$25.00 © 2014 SPIE and IS&T
Xiao-qing Luo, Zhan-cheng Zhang, and Xiao-jun Wu "Adaptive multistrategy image fusion method," Journal of Electronic Imaging 23(5), 053011 (22 September 2014). https://doi.org/10.1117/1.JEI.23.5.053011
Published: 22 September 2014
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CITATIONS
Cited by 6 scholarly publications.
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KEYWORDS
Image fusion

Image segmentation

Stationary wavelet transform

Medical imaging

Principal component analysis

Visualization

Image quality


CHORUS Article. This article was made freely available starting 22 September 2015

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