Low Illumination Video Image Enhancement
Due to weather conditions, brightness conditions, capture equipment and other factors, leads to video unclear or even abnormally confused, which is not conducive to monitoring, and can not meet the needs of applications. Based on the actual data of night video surveillance, this paper proposes a new...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
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| Series: | IEEE Photonics Journal |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9145629/ |
| _version_ | 1818556861887021056 |
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| author | Zhi Li Zhenhong Jia Jie Yang Nikola Kasabov |
| author_facet | Zhi Li Zhenhong Jia Jie Yang Nikola Kasabov |
| author_sort | Zhi Li |
| collection | DOAJ |
| description | Due to weather conditions, brightness conditions, capture equipment and other factors, leads to video unclear or even abnormally confused, which is not conducive to monitoring, and can not meet the needs of applications. Based on the actual data of night video surveillance, this paper proposes a new low illumination video image enhancement algorithm, which overcomes the existing problems. We analyze the characteristics of low illumination video image, and use HSV color space instead of traditional RGB space to enhance the robustness of video contrast and color distortion. At the same time, we use wavelet image fusion to highlight the details of video image, so the enhanced video has higher clarity and visual effect. Compared with other four algorithms, the proposed algorithm outperforms the above algorithms in subjective evaluation and objective evaluation. At the same time, compared with other algorithms, the proposed algorithm has faster processing time for each frame. Experiments show that the algorithm can effectively improve the overall brightness and contrast of video images, and avoid the over-enhancement of bright areas near the light source, which can meet the practical application requirements of video surveillance. |
| first_indexed | 2024-12-13T23:52:42Z |
| format | Article |
| id | doaj.art-b3d31a586c8a40749f19ca436c1437c3 |
| institution | Directory Open Access Journal |
| issn | 1943-0655 |
| language | English |
| last_indexed | 2024-12-13T23:52:42Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Photonics Journal |
| spelling | doaj.art-b3d31a586c8a40749f19ca436c1437c32022-12-21T23:26:43ZengIEEEIEEE Photonics Journal1943-06552020-01-0112411310.1109/JPHOT.2020.30109669145629Low Illumination Video Image EnhancementZhi Li0Zhenhong Jia1https://orcid.org/0000-0002-4578-6073Jie Yang2https://orcid.org/0000-0003-4433-7521Nikola Kasabov3https://orcid.org/0000-0003-4801-7162College of Information Science and Engineering, Xinjiang University, Urumuqi, ChinaCollege of Information Science and Engineering, Xinjiang University, Urumuqi, ChinaInstitute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, ChinaKnowledge Engineering and Discovery Research Institute, Auckland University of Technology, Auckland, New ZealandDue to weather conditions, brightness conditions, capture equipment and other factors, leads to video unclear or even abnormally confused, which is not conducive to monitoring, and can not meet the needs of applications. Based on the actual data of night video surveillance, this paper proposes a new low illumination video image enhancement algorithm, which overcomes the existing problems. We analyze the characteristics of low illumination video image, and use HSV color space instead of traditional RGB space to enhance the robustness of video contrast and color distortion. At the same time, we use wavelet image fusion to highlight the details of video image, so the enhanced video has higher clarity and visual effect. Compared with other four algorithms, the proposed algorithm outperforms the above algorithms in subjective evaluation and objective evaluation. At the same time, compared with other algorithms, the proposed algorithm has faster processing time for each frame. Experiments show that the algorithm can effectively improve the overall brightness and contrast of video images, and avoid the over-enhancement of bright areas near the light source, which can meet the practical application requirements of video surveillance.https://ieeexplore.ieee.org/document/9145629/Low illuminationVideo imageWavelet fusionHSV |
| spellingShingle | Zhi Li Zhenhong Jia Jie Yang Nikola Kasabov Low Illumination Video Image Enhancement IEEE Photonics Journal Low illumination Video image Wavelet fusion HSV |
| title | Low Illumination Video Image Enhancement |
| title_full | Low Illumination Video Image Enhancement |
| title_fullStr | Low Illumination Video Image Enhancement |
| title_full_unstemmed | Low Illumination Video Image Enhancement |
| title_short | Low Illumination Video Image Enhancement |
| title_sort | low illumination video image enhancement |
| topic | Low illumination Video image Wavelet fusion HSV |
| url | https://ieeexplore.ieee.org/document/9145629/ |
| work_keys_str_mv | AT zhili lowilluminationvideoimageenhancement AT zhenhongjia lowilluminationvideoimageenhancement AT jieyang lowilluminationvideoimageenhancement AT nikolakasabov lowilluminationvideoimageenhancement |