Single image haze removal using content‐adaptive dark channel and post enhancement
As a challenging problem, image haze removal plays an important role in computer vision applications. The dark channel prior has been widely studied for haze removal since it is simple and effective; however, it still suffers from over‐saturation, artefacts and dark‐look. To resolve these problems,...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-04-01
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| Series: | IET Computer Vision |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/iet-cvi.2013.0011 |
| _version_ | 1797685240752242688 |
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| author | Bo Li Shuhang Wang Jin Zheng Liping Zheng |
| author_facet | Bo Li Shuhang Wang Jin Zheng Liping Zheng |
| author_sort | Bo Li |
| collection | DOAJ |
| description | As a challenging problem, image haze removal plays an important role in computer vision applications. The dark channel prior has been widely studied for haze removal since it is simple and effective; however, it still suffers from over‐saturation, artefacts and dark‐look. To resolve these problems, this study proposes a method of single image haze removal using content‐adaptive dark channel and post enhancement. The main contributions of this work are as follows: first, an associative filter, which can transfer the structures of a reference image and the grey levels of a coarse image to the filtering output, is employed to compute the dark channel efficiently and effectively. Secondly, the dark channel confidence is utilised to restrict the dark channel based on the content of the image. Finally, a post enhancement method is devised to map the luminance of the restored haze‐free image with the preservation of local contrast. Experimental results demonstrate that the proposed method significantly improves the visibility of the hazy image. |
| first_indexed | 2024-03-12T00:41:18Z |
| format | Article |
| id | doaj.art-8361b0fd8d294ed1a3a8f397cc89d357 |
| institution | Directory Open Access Journal |
| issn | 1751-9632 1751-9640 |
| language | English |
| last_indexed | 2024-03-12T00:41:18Z |
| publishDate | 2014-04-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Computer Vision |
| spelling | doaj.art-8361b0fd8d294ed1a3a8f397cc89d3572023-09-15T07:13:10ZengWileyIET Computer Vision1751-96321751-96402014-04-018213114010.1049/iet-cvi.2013.0011Single image haze removal using content‐adaptive dark channel and post enhancementBo Li0Shuhang Wang1Jin Zheng2Liping Zheng3School of Computer Science and EngineeringBeihang UniversityXueYuan Road No. 37HaiDian DistrictBeijing100191People's Republic of ChinaSchool of Computer Science and EngineeringBeihang UniversityXueYuan Road No. 37HaiDian DistrictBeijing100191People's Republic of ChinaSchool of Computer Science and EngineeringBeihang UniversityXueYuan Road No. 37HaiDian DistrictBeijing100191People's Republic of ChinaSchool of Computer Science and EngineeringBeihang UniversityXueYuan Road No. 37HaiDian DistrictBeijing100191People's Republic of ChinaAs a challenging problem, image haze removal plays an important role in computer vision applications. The dark channel prior has been widely studied for haze removal since it is simple and effective; however, it still suffers from over‐saturation, artefacts and dark‐look. To resolve these problems, this study proposes a method of single image haze removal using content‐adaptive dark channel and post enhancement. The main contributions of this work are as follows: first, an associative filter, which can transfer the structures of a reference image and the grey levels of a coarse image to the filtering output, is employed to compute the dark channel efficiently and effectively. Secondly, the dark channel confidence is utilised to restrict the dark channel based on the content of the image. Finally, a post enhancement method is devised to map the luminance of the restored haze‐free image with the preservation of local contrast. Experimental results demonstrate that the proposed method significantly improves the visibility of the hazy image.https://doi.org/10.1049/iet-cvi.2013.0011image haze removalcontent adaptive dark channelcomputer visionassociative flltercoarse image grey levelimage flltering |
| spellingShingle | Bo Li Shuhang Wang Jin Zheng Liping Zheng Single image haze removal using content‐adaptive dark channel and post enhancement IET Computer Vision image haze removal content adaptive dark channel computer vision associative fllter coarse image grey level image flltering |
| title | Single image haze removal using content‐adaptive dark channel and post enhancement |
| title_full | Single image haze removal using content‐adaptive dark channel and post enhancement |
| title_fullStr | Single image haze removal using content‐adaptive dark channel and post enhancement |
| title_full_unstemmed | Single image haze removal using content‐adaptive dark channel and post enhancement |
| title_short | Single image haze removal using content‐adaptive dark channel and post enhancement |
| title_sort | single image haze removal using content adaptive dark channel and post enhancement |
| topic | image haze removal content adaptive dark channel computer vision associative fllter coarse image grey level image flltering |
| url | https://doi.org/10.1049/iet-cvi.2013.0011 |
| work_keys_str_mv | AT boli singleimagehazeremovalusingcontentadaptivedarkchannelandpostenhancement AT shuhangwang singleimagehazeremovalusingcontentadaptivedarkchannelandpostenhancement AT jinzheng singleimagehazeremovalusingcontentadaptivedarkchannelandpostenhancement AT lipingzheng singleimagehazeremovalusingcontentadaptivedarkchannelandpostenhancement |