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A single image dehazing model using total variation and inter-channel correlation. (English) Zbl 1448.94020
Summary: 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 [W. Wang et al., “A constrained total variation model for single image dehazing”, Pattern Recognition 80, 196–209 (2018; doi:10.1016/j.patcog.2018.03.009)]. 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.

MSC:
94A08 Image processing (compression, reconstruction, etc.) in information and communication theory
49J10 Existence theories for free problems in two or more independent variables
49N45 Inverse problems in optimal control
90C25 Convex programming
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