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Automatic Detection of Low Light Images in a Video Sequence Shot under Different Light Conditions

机译:自动检测在不同光照条件下拍摄的视频序列中的弱光图像

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摘要

Nocturnal insects have the ability to neurally sum visual signals in space and time to be able to see under very low light conditions. This ability shown by nocturnal insects has inspired many researchers to develop a night vision algorithm, that is capable of significantly improving the quality and reliability of digital images captured under very low light conditions. This algorithm however when applied to day time images rather degrades their quality. It is therefore not suitable to apply the night vision algorithms equally to an image stream with different light conditions. This paper introduces a quick method of automatically determining when to apply the nocturnal vision algorithm by analysing the cumulative intensity histogram of each image in the stream. The effectiveness of this method is demonstrated with relevant experiments in a good and acceptable way.
机译:夜间昆虫具有在空间和时间上对视觉信号进行神经求和的能力,从而能够在非常弱的光照条件下进行观察。夜间昆虫表现出的这种能力激发了许多研究人员开发夜视算法,该算法能够显着提高在非常弱的光照条件下捕获的数字图像的质量和可靠性。但是,将此算法应用于白天图像时,会降低其质量。因此,不适合将夜视算法平均应用于具有不同光照条件的图像流。本文通过分析流中每幅图像的累积强度直方图,介绍了一种自动确定何时应用夜间视觉算法的快速方法。通过相关实验以良好且可接受的方式证明了该方法的有效性。

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