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.

中文翻译：

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低照度视频图像增强

由于天气条件、亮度条件、采集设备等因素，导致视频不清晰甚至异常混乱，不利于监控，不能满足应用需求。本文基于夜间视频监控的实际数据，提出了一种新的低照度视频图像增强算法，克服了现有的问题。我们分析了低照度视频图像的特点，并使用HSV色彩空间代替传统的RGB空间来增强视频对比度和色彩失真的鲁棒性。同时，我们使用小波图像融合来突出视频图像的细节，因此增强后的视频具有更高的清晰度和视觉效果。与其他四种算法相比，所提算法在主观评价和客观评价方面均优于上述算法。同时，与其他算法相比，该算法对每一帧的处理时间更快。实验表明，该算法能够有效提高视频图像的整体亮度和对比度，避免光源附近亮区的过度增强，能够满足视频监控的实际应用需求。