煤矿提升机监控系统图像增强算法研究

Wei Zhang, Dongsheng Zuo, Congjiao Wang, Bing Sun
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引用次数: 1

摘要

矿井提升机监控的视频图像光线差、亮度低、粉尘大、对比度低,不利于监控视频图像。它们不能满足应用程序的需要。基于实际视频监控数据,提出了一种暗信道先验(DCP)方法与导图滤波相结合的视频图像增强算法。首先,分析了矿井提升系统视频图像的特点。然后,利用DCP技术对视频图像进行增强处理。引入了一种引导图像滤波算法,保证了视频的清晰度和视觉冲击力。将该方法与其他四种算法进行比较,其主观上和客观上都优于上述算法。实验表明,该技术能够成功地提高视频图像的整体清晰度和对比度,同时避免了光源附近明亮区域的过度增强,满足了视频监控的实际应用需求。
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Research on image enhancement algorithm for the monitoring system in coal mine hoist
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.
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