Single Image Dehazing Using Local Detail Enhancement

J. Ok, T. Jeong, C. Lee
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Abstract

Most existing single image dehazing algorithms require the estimation of atmospheric light using simple procedures based on error-prone assumptions. In this letter, a new dehazing method based on local detail enhancement is proposed to estimate atmospheric light and transmission map by considering local detail enhanced images as quasi-haze-free images. The proposed method is based on the decomposition model that interprets the transmission map as a base layer and the haze-free image as a detail-like layer. From a hazy image, local detail information is extracted using the local detail enhancement approach based on an edge preserving filter. Then, atmospheric lights and transmission maps for each color channel are estimated using Koschmieder’s law. The transmission map is refined using the dark channel prior and a guided filter. The experimental results show the proposed method can remove the layer of haze effectively and produce better performance than existing dehazing methods.
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使用局部细节增强的单个图像去雾
大多数现有的单幅图像去雾算法需要使用基于容易出错的假设的简单程序来估计大气光。本文提出了一种基于局部细节增强的去雾方法,将局部细节增强图像作为准无雾图像来估计大气光和透射图。该方法基于分解模型,将透射图解释为基础层,将无雾图像解释为类细节层。在模糊图像中,采用基于边缘保持滤波器的局部细节增强方法提取局部细节信息。然后,使用Koschmieder定律估计每个颜色通道的大气光和透射图。利用暗信道先验和引导滤波器对传输图进行细化。实验结果表明,该方法能有效去除雾霾层,效果优于现有的除雾方法。
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