快速雾去除夜间图像使用最大反射率先验

Jing Zhang, Yang Cao, Shuai Fang, Yu Kang, Changwen Chen
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引用次数: 114

摘要

在本文中,我们解决了从单个夜间图像中去除雾霾的问题,即使在存在不同颜色和不均匀照明的情况下。其核心思想在于一种新的最大反射率先验。首先介绍了夜间朦胧成像模型,该模型在直接衰减项和散射项中都包含了局部环境光照项。然后,我们提出了一个简单而有效的图像先验,最大反射率先验,以估计变化的环境照明。最大反射率先验是基于一个关键的观察:对于大多数白天无雾图像补丁,每个颜色通道在某些像素处具有非常高的强度。对于夜间雾霾图像,各颜色通道的局部最大强度主要由环境光照贡献。因此,我们可以直接估计环境照度和透射图,从而恢复高质量的无雾图像。在各种夜间朦胧图像上的实验结果证明了该方法的有效性。特别是,我们的方法具有计算效率的优势,比最先进的方法快10-100倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fast Haze Removal for Nighttime Image Using Maximum Reflectance Prior
In this paper, we address a haze removal problem from a single nighttime image, even in the presence of varicolored and non-uniform illumination. The core idea lies in a novel maximum reflectance prior. We first introduce the nighttime hazy imaging model, which includes a local ambient illumination item in both direct attenuation term and scattering term. Then, we propose a simple but effective image prior, maximum reflectance prior, to estimate the varying ambient illumination. The maximum reflectance prior is based on a key observation: for most daytime haze-free image patches, each color channel has very high intensity at some pixels. For the nighttime haze image, the local maximum intensities at each color channel are mainly contributed by the ambient illumination. Therefore, we can directly estimate the ambient illumination and transmission map, and consequently restore a high quality haze-free image. Experimental results on various nighttime hazy images demonstrate the effectiveness of the proposed approach. In particular, our approach has the advantage of computational efficiency, which is 10-100 times faster than state-of-the-art methods.
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