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An iterative defogging algorithm based on pixel-level atmospheric light map

机译:一种基于像素级大气光图的迭代缺点算法

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摘要

Most defogging algorithms often lead to the problem of sky oversaturation and non-sky brightness. In order to solve these problems, a dark channel iterative demisting algorithm based on pixel level atmospheric light map is proposed in this paper. Firstly, the algorithm in this paper obtains a pixel-level atmospheric light map based on the model of the relationship between fog density and depth of field. Secondly, the algorithm uses an iterative defogging method to control the optimal defogging degree, thereby restoring high-quality defogging images. The experimental results show that the image obtained by the algorithm in this paper is not only high in definition but also real-time, and the problems of sky oversaturation and non-sky brightness are effectively solved.
机译:大多数违规算法通常导致天空过大的问题和非天空亮度。为了解决这些问题,本文提出了一种基于像素级大气光图的暗信道迭代除算法。首先,本文中的算法基于雾密度与景深之间的关系模型获得像素级大气光图。其次,该算法使用迭代脱模方法来控制最佳缺点度,从而恢复高质量的脱模图像。实验结果表明,本文中的算法获得的图像不仅是高的定义,而且实时,并且有效地解决了天空过大的问题和天空亮度的问题。

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