Jia, Zhenhong

Kasabov, Nikola

Yang, Jie

Zhi, Li

English

Zhi Li

Zhenhong Jia

Jie Yang

Nikola Kasabov

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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 low illumination video image enhancement algorithm, which overcomes theexisting 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 theoverall 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

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https://pure.ulster.ac.uk/ws/files/79782598/ZhiLi_IEEE_final_version_July_2020.PDF

Low Illumination Video Image Enhancement

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