Open AccessImage fusion using multiscale edge‐preserving decomposition based on weighted least squares filter
Author(s) -
Jiang Yong,
Wang Minghui
Publication year - 2014
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2013.0429
Subject(s) - image fusion , artificial intelligence , filter (signal processing) , decomposition , enhanced data rates for gsm evolution , fusion , image (mathematics) , computer vision , least squares function approximation , computer science , pattern recognition (psychology) , composite image filter , mathematics , algorithm , statistics , chemistry , linguistics , philosophy , organic chemistry , estimator
For pixel‐level image fusion, the edges of the source images should be as much as possible integrated into the fused image because the human visual system is sensitive to them. In this study, the authors utilise the multiscale edge‐preserving decomposition (MSEPD) based on the weighted least squares filter to fuse the source images. In the authors’ method, first, the source images are decomposed by the MSEPD into a base image and a series of detail images, respectively. Then, the detail images of same scale are combined via the different fusion rules designed for different kinds of source images; the base images are combined via the average‐value rule. Finally, the fused image is constructed by adding the fused base image and detail images together. The proposed fusion method is verified on several kinds of images and compared with some methods based on multiscale decomposition. The experimental results indicate that the proposed method can provide better fused images, meanwhile manifesting a good edge‐preserving performance.