Radiance-Reflectance Combined Optimization and Structure-Guided ℓ0-Norm for Single Image Dehazing
- Authors
- Shin, Joongchol; Kim, Minseo; Paik, Joonki; Lee, Sangkeun
- Issue Date
- Jan-2020
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Keywords
- ℓ0-norm; gradient; dehazing; edge-preserving filtering; optimization; guided filtering
- Citation
- IEEE TRANSACTIONS ON MULTIMEDIA, v.22, no.1, pp 30 - 44
- Pages
- 15
- Journal Title
- IEEE TRANSACTIONS ON MULTIMEDIA
- Volume
- 22
- Number
- 1
- Start Page
- 30
- End Page
- 44
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/38193
- DOI
- 10.1109/TMM.2019.2922127
- ISSN
- 1520-9210
1941-0077
- Abstract
- Outdoor images are subject to degradation regarding contrast and color because atmospheric particles scatter incoming light to a camera. Existing haze models that employ model-based dehazing methods cannot avoid the dehazing artifacts. These artifacts include color distortion and overenhancement around object boundaries because of the incorrect transmission estimation from a depth error in the skyline and the wrong haze information, especially in bright objects. To overcome this problem, we present a novel optimization-based dehazing algorithm that combines radiance and reflectance components with an additional refinement using a structure-guided ℓ0-norm filter. More specifically, we first estimate a weak reflectance map and optimize the transmission map based on the estimated reflectance map. Next, we estimate the structure-guided ℓ0 transmission map to remove the dehazing artifacts. The experimental results show that the proposed method outperforms state-of-the-art algorithms in terms of qualitative and quantitative measures compared with simulated image pairs. In addition, the real-world enhancement results demonstrate that the proposed method can provide a high-quality image without undesired artifacts. Furthermore, the guided ℓ0-norm filter can remove textures while preserving edges for general image enhancement algorithms.
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Collections - Graduate School of Advanced Imaging Sciences, Multimedia and Film > Department of Imaging Science and Arts > 1. Journal Articles
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