Affiliation:
1. Shanghai Dianji University, Shanghai, China
2. Shanghai Maritime University, Shanghai, China
Abstract
As the mine hoist monitors video images with poor light, low brightness, heavy dust, and low contrast, the monitoring video images are not conducive to monitoring. They cannot meet the needs of applications. Based on actual video surveillance data, this paper proposes a dark channel prior (DCP) method integrated with a guided image filter video image enhancement algorithm. Firstly, we analyzed the characteristics of the mine hoist system’s video images. Then, the DCP technique was used to enhance the video images. A guided image filter algorithm was introduced to ensure that the video has more clarity and visual impact. Comparing the suggested method to the other four algorithms, it performed better both subjectively and objectively than the algorithms mentioned above. Experiments demonstrate that the proposed technique can successfully improve the entire clarity and contrast of video images while avoiding the over-enhancement of bright areas close to the light source, meeting the practical application requirements of video surveillance.
Funder
Shanghai Rising-Star Program
National Natural Science Foundation of China
Natural Science Foundation of Shanghai
Subject
Applied Mathematics,Control and Optimization,Instrumentation
Cited by
2 articles.
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