Single Fog Image Dehazing via Truncated Total Variation Method

Yin Gao, Yijing Su, Jun Li
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Abstract

Existing dehazing methods are usually to appear visual problems. In the paper, we put forward a truncated total variation method (TTV) to eliminate haze. A histogram analysis is firstly developed to obtain global atmospheric light. Then, using an adaptive boundary constraint TTV to optimize the transmission properly. Finally, a new DCP is presented to remove haze. Shown in experimental results, our method can outperform existent methods on the visual effect.
基于截断总变分法的单雾图像去雾
现有的除雾方法通常会出现视觉问题。本文提出了一种截断总变分法(TTV)来消除雾霾。首先提出了一种直方图分析方法来获取全球大气光。然后,利用自适应边界约束TTV对传输进行优化。最后,提出了一种新的DCP来去除雾霾。实验结果表明,我们的方法在视觉效果上优于现有的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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