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Infrared and visible image fusion based on nonsubsampled shearlet transform and fuzzy C-means clustering.
- Source :
- Journal of Electronic Imaging; Jul/Aug2018, Vol. 27 Issue 4, p1-9, 9p
- Publication Year :
- 2018
-
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. ©2018 SPIE and IS&T [DOI: 10.1117/1.JEI.27.4.043042] [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 10179909
- Volume :
- 27
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- Journal of Electronic Imaging
- Publication Type :
- Academic Journal
- Accession number :
- 131642577
- Full Text :
- https://doi.org/10.1117/1.JEI.27.4.043042