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On the Duality Between Retinex and Image Dehazing
- Source :
- IEEE/CVF Conference on Computer Vision and Pattern Recognition, Recercat. Dipósit de la Recerca de Catalunya, instname, CVPR
- Publication Year :
- 2018
-
Abstract
- Image dehazing deals with the removal of undesired loss of visibility in outdoor images due to the presence of fog. Retinex is a color vision model mimicking the ability of the Human Visual System to robustly discount varying illuminations when observing a scene under different spectral lighting conditions. Retinex has been widely explored in the computer vision literature for image enhancement and other related tasks. While these two problems are apparently unrelated, the goal of this work is to show that they can be connected by a simple linear relationship. Specifically, most Retinex-based algorithms have the characteristic feature of always increasing image brightness, which turns them into ideal candidates for effective image dehazing by directly applying Retinex to a hazy image whose intensities have been inverted. In this paper, we give theoretical proof that Retinex on inverted intensities is a solution to the image dehazing problem. Comprehensive qualitative and quantitative results indicate that several classical and modern implementations of Retinex can be transformed into competing image dehazing algorithms performing on pair with more complex fog removal methods, and can overcome some of the main challenges associated with this problem.<br />13 pages, 5 figures
- Subjects :
- FOS: Computer and information sciences
Brightness
Color vision
Computer science
Computer Vision and Pattern Recognition (cs.CV)
Computer Science - Computer Vision and Pattern Recognition
Image processing
02 engineering and technology
Retinex
Image color analysis
Image (mathematics)
Dehazing
0202 electrical engineering, electronic engineering, information engineering
Computer vision
Lighting
Color constancy
business.industry
Visibility (geometry)
020206 networking & telecommunications
Computational modeling
Atmospheric modeling
Feature (computer vision)
Human visual system model
Task analysis
020201 artificial intelligence & image processing
Artificial intelligence
business
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- IEEE/CVF Conference on Computer Vision and Pattern Recognition, Recercat. Dipósit de la Recerca de Catalunya, instname, CVPR
- Accession number :
- edsair.doi.dedup.....95331b73d2fbedfab74760350ef780f7