Single-image dehazing method based on Rayleigh Scattering and adaptive color compensation

We propose a Rayleigh Scattering and adaptive color compensation method. It capitalizes on the brightness and color differentials between the regions where DCP has failed within images for effective regional segmentation. First, we added B-channel compensation to the atmospheric illumination, made a simple evaluation of the B channel through the atmospheric illumination of the R channel and the G channel. It repeatedly iterated to obtain and repaired the atmospheric illumination of the B channel, which eliminates the color dilution. Secondly, we obtained the dark channel image and the bright channel image, and jointly evaluated the failure point of the dark channel prior method to select the area with inaccurate transmission. This can select the areas which need re-estimate the transmission. This step improves the image quality of the area and repairs the image details. Finally, we validated the effectiveness and resilience of the proposed method through comprehensive experiments. It is conducted across diverse scenarios, involving the adjustment of various parameters.

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Publication Details

Journal
PLoS ONE
Published
2025-03-20
DOI
https://doi.org/10.1371/journal.pone.0315176
Citations
1
Primary Topic
Image Enhancement Techniques
Type
article
Field-Weighted Citation Impact
1.28

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Single-image dehazing method based on Rayleigh Scattering and adaptive color compensation

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Single-image dehazing method based on Rayleigh Scattering and adaptive color compensation

Yan Zhou, Jinghua Zhao, Yingying Zhang, Xin Guo, Qilong Sun, Mingchen Sun, Yiyang Qiao
article en
1 citations

Abstract

We propose a Rayleigh Scattering and adaptive color compensation method. It capitalizes on the brightness and color differentials between the regions where DCP has failed within images for effective regional segmentation. First, we added B-channel compensation to the atmospheric illumination, made a simple evaluation of the B channel through the atmospheric illumination of the R channel and the G channel. It repeatedly iterated to obtain and repaired the atmospheric illumination of the B channel, which eliminates the color dilution. Secondly, we obtained the dark channel image and the bright channel image, and jointly evaluated the failure point of the dark channel prior method to select the area with inaccurate transmission. This can select the areas which need re-estimate the transmission. This step improves the image quality of the area and repairs the image details. Finally, we validated the effectiveness and resilience of the proposed method through comprehensive experiments. It is conducted across diverse scenarios, involving the adjustment of various parameters.

PLoS ONEVol. 20(3)
Jilin Normal University (CN), Jilin University (CN), Jilin Province Science and Technology Department (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 22%
Image Enhancement Techniques
1.28
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