Saliency-driven single image haze removal method based on reliable airlight and transmission
Saliency-driven single image haze removal method based on reliable airlight and transmission
复制标题
基于可靠空气光和传输的显着性驱动的单幅图像去雾方法
DOI：
10.1117/1.jei.27.2.023038
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发表时间：
2018-04
影响因子：
1.1
通讯作者：
Zhang Zhe
中科院分区：
文献类型：
--
作者：
Zhang Libao;Wang Xiaohan;She Chen;Wang Shiyi;Zhang Zhe
除雾技术是近年来研究的热点问题，各种除雾方法被提出.暗通道先验（DCP）是最有效的去雾方法之一。然而，当处理包含大的白色对象的图像时，DCP经常将白色对象误认为不透明的雾。它会导致对空气光的高估和对透射率的低估，从而使去雾结果产生严重的颜色失真。针对上述问题，本文将显著性检测引入到去雾中，以获得更好的恢复图像。我们首先提出了一种可靠的空气光估计的方法。然后，提出了一种模糊图像的显著性先验，通过显著性检测可以区分白色目标和稠密模糊目标。在显著性先验的基础上，可以从包含大的白色物体的图像中获得准确的空气光和正确的透射图，最终可以成功地恢复这些图像。实验结果表明，该方法在处理含有大面积白色物体的图像时，具有很大的优越性。
Haze removal has become an attractive topic in recent years and several dehazing methods are proposed. Dark channel prior (DCP) is one of the most effective dehazing approaches. However, when dealing with images containing large white objects, DCP often mistakes white objects for opaque haze. It will cause the airlight to be overestimated and the transmission to be underestimated, and thus the dehazing results have serious color distortion. In view of the above problem, saliency detection is introduced into haze removal to obtain better restored images in this paper. We first propose a method for reliable airlight estimation. Then, a saliency prior is presented for hazy images, which can distinguish white objects from dense haze by saliency detection. On the basis of saliency prior, both accurate airlight and a correct transmission map can be obtained from images containing large white objects, and finally these images can be restored successfully. The experimental results illustrate that our proposed method has great superiority in color recovery compared with other state-of-art methods when dealing with images containing large white objects.
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DOI：
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发表时间：
2003
期刊：
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影响因子：
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DOI：
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