用于夜间监视的照明和基于运动的视频增强

Jing Li, S.Z. Li, Q. Pan, Tao Yang
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引用次数: 35

摘要

本文提出了一种用于夜间监控的低照度视频的上下文增强方法。该算法的独特之处在于能够提取和保持增强图像中高亮区域或低对比度运动物体等有意义的信息,同时通过融合白天背景图像恢复周围的场景信息。一个主要的挑战是如何从夜间视频序列中提取有意义的区域。为了解决这一问题,提出了一种新的双向提取方法。在真实数据评价实验中,成功提取了夜间视频的显著信息,并将背景场景与夜间图像平滑融合,为观察者呈现增强的监控视频。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Illumination and motion-based video enhancement for night surveillance
This work presents a context enhancement method of low illumination video for night surveillance. A unique characteristic of the algorithm is its ability to extract and maintenance the meaningful information like highlight area or moving objects with low contrast in the enhanced image, meanwhile recover the surrounding scene information by fusing the daytime background image. A main challenge comes from the extraction of meaningful area in the night video sequence. To address this problem, a novel bidirectional extraction approach is presented. In evaluation experiments with real data, the notable information of the night video is extracted successfully and the background scene is fused smoothly with the night images to show enhanced surveillance video for observers.
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