Abstract

This paper proposes a new single-image dehazing method, which is an important preprocessing step in vision applications to overcome the limitations of the conventional dark channel prior. The dark channel prior has a tendency to underestimate transmissions of bright regions or objects that can generate color distortions during the process of dehazing. In order to suppress the distortions in a large sky area or a bright white object, the sky probabilities and the white-object probabilities calculated in the non-sky area are proposed. The sky area is detected by combining the advantages of a region-based and a boundary-based sky segmentation in order to consider various sky shapes in road scenes. The performance of the proposed methods is evaluated using synthetic and real-world datasets. When compared to conventional methods in the reviewed literature, the proposed method produces significant improvements concerning visual and numerical criteria.

Highlights

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  • These results prove that the proposed method is effective parison cannot be made due to the difference in implementation, the efficiency of the pro‐

  • A method to recover images from hazy input images was presented. To this end, dehazing was performed based on dark channel prior (DCP), which is theCai most studied in this field, et al Proposed and sky probabilities and white‐object probabilities were proposed to solve oversatura‐

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Summary

Introduction

Citation: Kim, C. RobustSingle-Image Dehazing. Electronics2021, 10, 2636. https://doi.org/10.3390/electronics10212636Academic Editor: Chiman KwanReceived: 21 September 2021Accepted: 26 October 2021Published: 28 October 2021Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.Licensee MDPI, Basel, Switzerland.Attribution (CC BY) license (https://

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