Infrared and visible image fusion based on nonsubsampled shearlet transform and fuzzy C-means clustering

Jiamin Gong; Mengle Xue; Fan Ren; Zhe Ding; Siping Li; Yujie Hou; Qing Cai

doi:10.1117/1.JEI.27.4.043042

10 August 2018 Infrared and visible image fusion based on nonsubsampled shearlet transform and fuzzy C-means clustering

Jiamin Gong, Mengle Xue, Fan Ren, Zhe Ding, Siping Li, Yujie Hou, Qing Cai

Author Affiliations +

Journal of Electronic Imaging, Vol. 27, Issue 4, 043042 (August 2018). https://doi.org/10.1117/1.JEI.27.4.043042

Abstract

To preserve more useful information in visible and infrared images and improve the quality of the fused image, a method based on the nonsubsampled shearlet transform (NSST) and fuzzy C-means clustering is proposed. First, the source images are decomposed by NSST so as to get their own low- and high-frequency subbands. Second, the low-frequency subbands are divided into the infrared target part and the background part by fuzzy C-means clustering while different fusion rules are applied to the infrared target part and background part, respectively. Then, a choose-max fusion rule based on the sum-modified Laplacian of source images and local energy of coefficient is proposed to integrate the high-frequency subbands. Finally, the fused image is obtained by inverse NSST. The comparison experiment with the other three state-of-the-art fusion methods shows that the proposed method has good subjective visual effects and superior objective evaluations.

Citation Download Citation

Jiamin Gong, Mengle Xue, Fan Ren, Zhe Ding, Siping Li, Yujie Hou, and Qing Cai "Infrared and visible image fusion based on nonsubsampled shearlet transform and fuzzy C-means clustering," Journal of Electronic Imaging 27(4), 043042 (10 August 2018). https://doi.org/10.1117/1.JEI.27.4.043042

Received: 28 March 2018; Accepted: 18 July 2018; Published: 10 August 2018

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