Image Dehazing Based on Accurate Estimation of Transmission in the Atmospheric Scattering Model
Image dehazing is a challenging and highly desired technology in computer vision applications. The dark channel prior (DCP) has been considered to be an efficient dehazing technique in recent years. However, the invalidation of DCP can induce unreliable estimation of transmission, resulting in inacc...
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| Format: | Article |
| Language: | English |
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IEEE
2017-01-01
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| Series: | IEEE Photonics Journal |
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| Online Access: | https://ieeexplore.ieee.org/document/7976290/ |
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| author | Guoling Bi Jianyue Ren Tianjiao Fu Ting Nie Changzheng Chen Nan Zhang |
| author_facet | Guoling Bi Jianyue Ren Tianjiao Fu Ting Nie Changzheng Chen Nan Zhang |
| author_sort | Guoling Bi |
| collection | DOAJ |
| description | Image dehazing is a challenging and highly desired technology in computer vision applications. The dark channel prior (DCP) has been considered to be an efficient dehazing technique in recent years. However, the invalidation of DCP can induce unreliable estimation of transmission, resulting in inaccurate color information recovery, halo artifacts, and block effect. In this paper, a novel brightness map is proposed based on the observation on outdoor haze-free/haze images that can reflect the brightness information and the light reflection ability of the scene, furthermore, the relationship between DCP and the brightness map is given in mathematical model. The proposed algorithm can compensate for the DCP effectively, estimate the transmission map accurately, get the global atmospheric light adaptively and segment the image automatically. Using multiscale guided filter refine transmission map, the halo artifacts are able to be avoided in the scene depth of a sudden change. A series of experiments are additionally implemented to demonstrate that the proposed algorithm can obtain high-quality haze-free images with abundant distinguished details, low color distortion, and little halo artifacts that can outperform or be comparable with four state-of-the-art haze removal algorithms. |
| format | Article |
| id | doaj-art-d19eebe702bd477b896bc3784d4bd0ff |
| institution | Kabale University |
| issn | 1943-0655 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Photonics Journal |
| spelling | doaj-art-d19eebe702bd477b896bc3784d4bd0ff2025-08-20T03:31:16ZengIEEEIEEE Photonics Journal1943-06552017-01-019411810.1109/JPHOT.2017.27261077976290Image Dehazing Based on Accurate Estimation of Transmission in the Atmospheric Scattering ModelGuoling Bi0Jianyue Ren1Tianjiao Fu2Ting Nie3Changzheng Chen4Nan Zhang5Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, ChinaChangchun Observatory, National Astronomical Observatories, Chinese Academy of Sciences, Changchun, ChinaImage dehazing is a challenging and highly desired technology in computer vision applications. The dark channel prior (DCP) has been considered to be an efficient dehazing technique in recent years. However, the invalidation of DCP can induce unreliable estimation of transmission, resulting in inaccurate color information recovery, halo artifacts, and block effect. In this paper, a novel brightness map is proposed based on the observation on outdoor haze-free/haze images that can reflect the brightness information and the light reflection ability of the scene, furthermore, the relationship between DCP and the brightness map is given in mathematical model. The proposed algorithm can compensate for the DCP effectively, estimate the transmission map accurately, get the global atmospheric light adaptively and segment the image automatically. Using multiscale guided filter refine transmission map, the halo artifacts are able to be avoided in the scene depth of a sudden change. A series of experiments are additionally implemented to demonstrate that the proposed algorithm can obtain high-quality haze-free images with abundant distinguished details, low color distortion, and little halo artifacts that can outperform or be comparable with four state-of-the-art haze removal algorithms.https://ieeexplore.ieee.org/document/7976290/Image dehazingbrightness maptransmission estimatedark channel prior |
| spellingShingle | Guoling Bi Jianyue Ren Tianjiao Fu Ting Nie Changzheng Chen Nan Zhang Image Dehazing Based on Accurate Estimation of Transmission in the Atmospheric Scattering Model IEEE Photonics Journal Image dehazing brightness map transmission estimate dark channel prior |
| title | Image Dehazing Based on Accurate Estimation of Transmission in the Atmospheric Scattering Model |
| title_full | Image Dehazing Based on Accurate Estimation of Transmission in the Atmospheric Scattering Model |
| title_fullStr | Image Dehazing Based on Accurate Estimation of Transmission in the Atmospheric Scattering Model |
| title_full_unstemmed | Image Dehazing Based on Accurate Estimation of Transmission in the Atmospheric Scattering Model |
| title_short | Image Dehazing Based on Accurate Estimation of Transmission in the Atmospheric Scattering Model |
| title_sort | image dehazing based on accurate estimation of transmission in the atmospheric scattering model |
| topic | Image dehazing brightness map transmission estimate dark channel prior |
| url | https://ieeexplore.ieee.org/document/7976290/ |
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