Authors:
Dongbin Xu
1
;
Chuangbai Xiao
1
and
Jing Yu
2
Affiliations:
1
Beijing University of Technology, China
;
2
Department of Electronic Engineering, Tsinghua University, China
Keyword(s):
Defog, Retinex, Image Enhancement.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Enhancement and Restoration
;
Image Formation and Preprocessing
;
Image Quality
Abstract:
Bad weather, such as fog and haze, can significantly degrade the imaging quality, which becomes a major problem for many applications of computer vision. In this paper, we propose a novel color-preserving defog method based on the Retinex theory, using a single image as an input without user interactions. In the proposed method, we apply the Retinex theory to fog/haze removal form foggy/hazy images, and conceive a new strategy of fog/haze estimation. Experiment results demonstrate that the proposed method can not only remove fog or haze present in foggy or hazy images, but also restore real color of clear-day counterparts, without color distortion. Besides, the proposed method has very fast implementation.