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Journal of Applied Remote Sensing

Weber-aware weighted mutual information evaluation for infrared–visible image fusion
Author(s): Xiaoyan Luo; Shining Wang; Ding Yuan
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Paper Abstract

A performance metric for infrared and visible image fusion is proposed based on Weber’s law. To indicate the stimulus of source images, two Weber components are provided. One is differential excitation to reflect the spectral signal of visible and infrared images, and the other is orientation to capture the scene structure feature. By comparing the corresponding Weber component in infrared and visible images, the source pixels can be marked with different dominant properties in intensity or structure. If the pixels have the same dominant property label, the pixels are grouped to calculate the mutual information (MI) on the corresponding Weber components between dominant source and fused images. Then, the final fusion metric is obtained via weighting the group-wise MI values according to the number of pixels in different groups. Experimental results demonstrate that the proposed metric performs well on popular image fusion cases and outperforms other image fusion metrics.

Paper Details

Date Published: 13 October 2016
PDF: 13 pages
J. Appl. Rem. Sens. 10(4) 045004 doi: 10.1117/1.JRS.10.045004
Published in: Journal of Applied Remote Sensing Volume 10, Issue 4
Show Author Affiliations
Xiaoyan Luo, BeiHang Univ. (China)
Shining Wang, China Waterborne Transport Research Institute (China)
Ding Yuan, BeiHang Univ. (China)

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