Open AccessSingle image dehazing using local linear fusion
Author(s) -
Gao Yakun,
Chen Haiyan,
Li Haibin,
Zhang Wenming
Publication year - 2018
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.2017.0570
Subject(s) - artificial intelligence , computer vision , image restoration , computer science , image fusion , image (mathematics) , distortion (music) , haze , contrast (vision) , fusion , image processing , physics , linguistics , philosophy , amplifier , computer network , bandwidth (computing) , meteorology
The authors propose a new single image dehazing method. Different from image restoration and image enhancement method, their method is based on the idea of image fusion. Image dehazing is to remove the influence of the haze between the scene and the camera. First, combined with the depth information, the haze layer is subtracted in the hazy image to improve the colour saturation, which produces the first input image. Then, the gamma correction is used on the grey image. Second, the details of the gamma correction image are enhanced to produce the second input image. Finally, the two input images are fused by local linear model to obtain the final restored image. Experimental results show that the restored image has high contrast, rich details, and without colour distortion in the sky area.