Weber-aware weighted mutual information evaluation for infrared–visible image fusion

Xiaoyan Luo; Shining Wang; Ding Yuan

doi:10.1117/1.JRS.10.045004

13 October 2016 Weber-aware weighted mutual information evaluation for infrared–visible image fusion

Xiaoyan Luo, Shining Wang, Ding Yuan

Author Affiliations +

Funded by: Natural Science Foundation of China, National Basic Research Program of China, Fundamental Research Funds for the Central Universities

Journal of Applied Remote Sensing, Vol. 10, Issue 4, 045004 (October 2016). https://doi.org/10.1117/1.JRS.10.045004

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.

Citation Download Citation

Xiaoyan Luo, Shining Wang, and Ding Yuan "Weber-aware weighted mutual information evaluation for infrared–visible image fusion," Journal of Applied Remote Sensing 10(4), 045004 (13 October 2016). https://doi.org/10.1117/1.JRS.10.045004

Published: 13 October 2016

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