Outdoor images are often degraded by haze, causing a change of image contrast and color values. In this paper, we propose a novel variational model for the removal of haze in a single color image, by incorporating an inter-channel correlation term into the total variation based model in Wang et al. (Pattern Recognit 80:196–209, 2018 ). The proposed model enables both color and gray-valued transmission maps, contributing to its broad applications, and its convergence analysis is also provided. To realize the proposed model, we adopt an alternating minimization algorithm, and then the alternating direction method of multipliers is employed for solving subproblems. These result in an efficient iterative algorithm, with its convergence proven. Numerical experiments validate the outstanding performance of the proposed model compared to the state-of-the-art methods.

中文翻译：

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使用总变异和通道间相关的单幅图像去雾模型

室外图像经常因雾霾而退化，导致图像对比度和颜色值发生变化。在本文中，我们提出了一种新的变分模型，用于去除单色图像中的雾霾，通过将通道间相关项合并到 Wang 等人的基于总变分的模型中。（模式识别 80：196-209，2018 年）。所提出的模型支持彩色和灰度值传输图，有助于其广泛的应用，并且还提供了其收敛分析。为了实现所提出的模型，我们采用交替最小化算法，然后采用乘法器交替方向法求解子问题。这些导致了有效的迭代算法，其收敛性得到了证明。