Detail Preserving Low Illumination Image and Video Enhancement Algorithm Based on Dark Channel Prior
In low illumination situations, insufficient light in the monitoring device results in poor visibility of effective information, which cannot meet practical applications. To overcome the above problems, a detail preserving low illumination video image enhancement algorithm based on dark channel prio...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-12-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/22/1/85 |
| _version_ | 1827667642098384896 |
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| author | Lingli Guo Zhenhong Jia Jie Yang Nikola K. Kasabov |
| author_facet | Lingli Guo Zhenhong Jia Jie Yang Nikola K. Kasabov |
| author_sort | Lingli Guo |
| collection | DOAJ |
| description | In low illumination situations, insufficient light in the monitoring device results in poor visibility of effective information, which cannot meet practical applications. To overcome the above problems, a detail preserving low illumination video image enhancement algorithm based on dark channel prior is proposed in this paper. First, a dark channel refinement method is proposed, which is defined by imposing a structure prior to the initial dark channel to improve the image brightness. Second, an anisotropic guided filter (AnisGF) is used to refine the transmission, which preserves the edges of the image. Finally, a detail enhancement algorithm is proposed to avoid the problem of insufficient detail in the initial enhancement image. To avoid video flicker, the next video frames are enhanced based on the brightness of the first enhanced frame. Qualitative and quantitative analysis shows that the proposed algorithm is superior to the contrast algorithm, in which the proposed algorithm ranks first in average gradient, edge intensity, contrast, and patch-based contrast quality index. It can be effectively applied to the enhancement of surveillance video images and for wider computer vision applications. |
| first_indexed | 2024-03-10T03:22:09Z |
| format | Article |
| id | doaj.art-7edf2b74411b4b36ada09622ecf2443c |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T03:22:09Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-7edf2b74411b4b36ada09622ecf2443c2023-11-23T12:16:41ZengMDPI AGSensors1424-82202021-12-012218510.3390/s22010085Detail Preserving Low Illumination Image and Video Enhancement Algorithm Based on Dark Channel PriorLingli Guo0Zhenhong Jia1Jie Yang2Nikola K. Kasabov3College of Information Science and Engineering, Xinjiang University, Urumqi 830046, ChinaCollege of Information Science and Engineering, Xinjiang University, Urumqi 830046, ChinaInstitute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai 200400, ChinaKnowledge Engineering and Discovery Research Institute, Auckland University of Technology, Auckland 1020, New ZealandIn low illumination situations, insufficient light in the monitoring device results in poor visibility of effective information, which cannot meet practical applications. To overcome the above problems, a detail preserving low illumination video image enhancement algorithm based on dark channel prior is proposed in this paper. First, a dark channel refinement method is proposed, which is defined by imposing a structure prior to the initial dark channel to improve the image brightness. Second, an anisotropic guided filter (AnisGF) is used to refine the transmission, which preserves the edges of the image. Finally, a detail enhancement algorithm is proposed to avoid the problem of insufficient detail in the initial enhancement image. To avoid video flicker, the next video frames are enhanced based on the brightness of the first enhanced frame. Qualitative and quantitative analysis shows that the proposed algorithm is superior to the contrast algorithm, in which the proposed algorithm ranks first in average gradient, edge intensity, contrast, and patch-based contrast quality index. It can be effectively applied to the enhancement of surveillance video images and for wider computer vision applications.https://www.mdpi.com/1424-8220/22/1/85dark channel priorimage detail preservinglow illuminationimagesvideo |
| spellingShingle | Lingli Guo Zhenhong Jia Jie Yang Nikola K. Kasabov Detail Preserving Low Illumination Image and Video Enhancement Algorithm Based on Dark Channel Prior Sensors dark channel prior image detail preserving low illumination images video |
| title | Detail Preserving Low Illumination Image and Video Enhancement Algorithm Based on Dark Channel Prior |
| title_full | Detail Preserving Low Illumination Image and Video Enhancement Algorithm Based on Dark Channel Prior |
| title_fullStr | Detail Preserving Low Illumination Image and Video Enhancement Algorithm Based on Dark Channel Prior |
| title_full_unstemmed | Detail Preserving Low Illumination Image and Video Enhancement Algorithm Based on Dark Channel Prior |
| title_short | Detail Preserving Low Illumination Image and Video Enhancement Algorithm Based on Dark Channel Prior |
| title_sort | detail preserving low illumination image and video enhancement algorithm based on dark channel prior |
| topic | dark channel prior image detail preserving low illumination images video |
| url | https://www.mdpi.com/1424-8220/22/1/85 |
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