Referenceless perceptual image defogging
- Authors
- Choi, L.K.; You, J.; Bovik, A.C.
- Issue Date
- 2014
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Keywords
- defog; fog aware; visibility enhancement
- Citation
- Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation, pp.165 - 168
- Journal Title
- Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation
- Start Page
- 165
- End Page
- 168
- URI
- https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/16427
- DOI
- 10.1109/SSIAI.2014.6806055
- ISSN
- 0000-0000
- Abstract
- We propose a referenceless perceptual defog and visibility enhancement model based on multiscale fog aware statistical features. Our model operates on a single foggy image and uses a set of fog aware weight maps to improve the visibility of foggy regions. The proposed defog and visibility enhancer makes use of statistical regularities observed in foggy and fog-free images to extract the most visible information from three processed image results: one white balanced and two contrast enhanced images. Perceptual fog density, fog aware luminance, contrast, saturation, chrominance, and saliency weight maps smoothly blend these via a Laplacian pyramid. Evaluation on a variety of foggy images shows that the proposed model achieves better results for darker, denser foggy images as well as on standard defog test images. © 2014 IEEE.
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