V. Saminadan, P. Aishwarya, M. Manimegalai, M. Nivedhitha, G. Subhapriya
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引用次数: 6

摘要

在恶劣的天气条件下,室外场景的图像通常会下降,从而导致图像模糊。本文采用基于像素的暗通道先验和基于像素的亮通道先验两种图像先验来去除模糊图像中的雾霾。在此基础上,结合雾霾成像模型,通过雾霾密度分析估算大气光,并求出透射图。由于传输图存在光晕和块伪影,我们采用导频滤波对传输图进行细化。制导滤波器的输出是制导图像的线性变换。引导图像可以是输入图像本身,也可以是另一个不同的图像。在我们的案例中,引导图像是模糊图像。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient image dehazing based on pixel based dark channel prior and guided filter
Images of outdoor scenes are usually degraded under bad weather conditions, which results in a hazy image. In this paper, two image priors, called the pixel-based dark channel prior and the pixel-based bright channel prior are used to remove haze from a hazy image. Based on the two priors with the haze imaging model, the atmospheric light is estimated via haze density analysis followed by finding the transmission map. Since the transmission map suffers from halos and block artifacts, we refine it via guided filter. The output of a guided filter is a linear transform of the guidance image. Guidance image can be the input image itself or another different image. In our case Guidance image is hazy image.
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