Image Defogging Algorithm Based on Sky Region Segmentation and Dark Channel Prior

Jiang Zuyun (), Sun Xiangdong () and Wang Xiaochun ()
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Jiang Zuyun: College of Sciences, Beijing Forestry University, Beijing100083, China
Sun Xiangdong: College of Sciences, North China University of Technology, Beijing100144, China
Wang Xiaochun: College of Sciences, Beijing Forestry University, Beijing100083, China

Journal of Systems Science and Information, 2020, vol. 8, issue 5, 476-486

Abstract: Based on image segmentation and the dark channel prior, this paper proposes a fog removal algorithm in the HSI color space. Usually, the dark channel prior based defogging methods easily produce color distortion and halo effect when applied on images with a large sky area, because the sky region does not meet the prior assumption. For this reason, our method presents a new threshold sky region segmentation algorithm using the initial transmission map of the intensity component I. Based on the segmentation result, the initial transmission map is modified in turn, and finally refined by the guided filter. The saturation components S is reconstructed using the low frequencies of the V-transform to reduce noise, and stretched by multiplying a constant related to the initial transmission map. Experimental results show that the proposed algorithm has low time complexity and compelling fog removal result in both visual effect and quantitative measurement.

Keywords: dark channel prior; image haze removal; image segmentation; transmission map; V-transform (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:bpj:jossai:v:8:y:2020:i:5:p:476-486:n:6

DOI: 10.21078/JSSI-2020-476-11

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