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Pattern Recognition and Image Analysis

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01.07.2020 | APPLIED PROBLEMS

Improved Single Image Haze Removal for Intelligent Driving

verfasst von: Yi Lai, Q. Wang, R. Chen

Erschienen in: Pattern Recognition and Image Analysis | Ausgabe 3/2020

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Abstract

Haze often degrades the contrast and limits the visibility of scenes, and as a result it has a negative impact on the safe driving of intelligent vehicles. In order to solve this problem and enhance the quality of hazy images, this paper proposes an improved single image haze removal method. The main works include two parts. On the one hand, an improved atmospheric light estimation method is addressed to achieve an accurate estimation of the atmospheric light. On the other hand, the transmission map is refined with a composite filter using bilateral one followed by adaptive parameter adjustment on the transmission function. The experimental results show that the presented approach can obtain substantial improvements on the color and the detail recovery on both synthetic and real-world datasets.

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Titel: Improved Single Image Haze Removal for Intelligent Driving
verfasst von: Yi Lai
Q. Wang
R. Chen
Publikationsdatum: 01.07.2020
Verlag: Pleiades Publishing
Erschienen in: Pattern Recognition and Image Analysis / Ausgabe 3/2020
Print ISSN: 1054-6618
Elektronische ISSN: 1555-6212
DOI: https://doi.org/10.1134/S1054661820030177

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