A NEW METHOD FOR DEHAZING OF UAV REMOTE SENSING IMAGES BASED ON IMPROVED DARK CHANNEL PRIOR

Aiming to solve the problem of loss of important image information, such as blurred details and low contrast, caused by fog, haze and other meteorological influences in the slope monitoring process of UAV remote sensing images, a new method of improving dark channel image dehazing based on channel-w...

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Main Authors: X. L. Liu, T. Zhang, Y. H. Liu, R. J. Wang
Format: Article
Language:English
Published: Copernicus Publications 2022-10-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLVIII-3-W1-2022/31/2022/isprs-archives-XLVIII-3-W1-2022-31-2022.pdf
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author X. L. Liu
T. Zhang
Y. H. Liu
R. J. Wang
author_facet X. L. Liu
T. Zhang
Y. H. Liu
R. J. Wang
author_sort X. L. Liu
collection DOAJ
description Aiming to solve the problem of loss of important image information, such as blurred details and low contrast, caused by fog, haze and other meteorological influences in the slope monitoring process of UAV remote sensing images, a new method of improving dark channel image dehazing based on channel-weighted analysis and compensation function is proposed by a training of multilayer perceptron (MLP) in this study. First, based on the dark channel prior principle, the original hazy UAV image is mapped to obtain the estimated values of atmospheric light and rough transmittance. Next, by counting the RGB three-channel values of the pixels in the high-brightness regions, and analyzing the scattering of the RGB three-channel values in the haze, a color recovery module of atmospheric light is constructed, and the estimated value of atmospheric light is optimized. Then, according to the global transmittance, the compensation boundary value is determined and a functional relationship between different brightness regions and the increment of transmittance is established as a compensation function to optimize the rough transmittance. Finally, perform secondary optimization on the rough transmittance with the multi-layer perceptron (MLP) to obtain a smoother transmittance value. The experimental results show that the image processed by the proposed method has good contrast. The color saturation and authenticity are effectively maintained. And the detailed information of the mountain recorded by the image is better restored, which can provide a real data basis for slope monitoring.
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spelling doaj.art-9b0fc1072628456cad6453bb9fd5cbb62022-12-22T03:54:02ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342022-10-01XLVIII-3-W1-2022313710.5194/isprs-archives-XLVIII-3-W1-2022-31-2022A NEW METHOD FOR DEHAZING OF UAV REMOTE SENSING IMAGES BASED ON IMPROVED DARK CHANNEL PRIORX. L. Liu0T. Zhang1Y. H. Liu2R. J. Wang3Key Laboratory for Urban Geomatics of National Administration of Surveying, Mapping and Geoinformation, Beijing University of Civil Engineering and Architecture, 1 Zhanlanguan Road, Beijing, 100048, P.R. ChinaKey Laboratory for Urban Geomatics of National Administration of Surveying, Mapping and Geoinformation, Beijing University of Civil Engineering and Architecture, 1 Zhanlanguan Road, Beijing, 100048, P.R. ChinaKey Laboratory for Urban Geomatics of National Administration of Surveying, Mapping and Geoinformation, Beijing University of Civil Engineering and Architecture, 1 Zhanlanguan Road, Beijing, 100048, P.R. ChinaKey Laboratory for Urban Geomatics of National Administration of Surveying, Mapping and Geoinformation, Beijing University of Civil Engineering and Architecture, 1 Zhanlanguan Road, Beijing, 100048, P.R. ChinaAiming to solve the problem of loss of important image information, such as blurred details and low contrast, caused by fog, haze and other meteorological influences in the slope monitoring process of UAV remote sensing images, a new method of improving dark channel image dehazing based on channel-weighted analysis and compensation function is proposed by a training of multilayer perceptron (MLP) in this study. First, based on the dark channel prior principle, the original hazy UAV image is mapped to obtain the estimated values of atmospheric light and rough transmittance. Next, by counting the RGB three-channel values of the pixels in the high-brightness regions, and analyzing the scattering of the RGB three-channel values in the haze, a color recovery module of atmospheric light is constructed, and the estimated value of atmospheric light is optimized. Then, according to the global transmittance, the compensation boundary value is determined and a functional relationship between different brightness regions and the increment of transmittance is established as a compensation function to optimize the rough transmittance. Finally, perform secondary optimization on the rough transmittance with the multi-layer perceptron (MLP) to obtain a smoother transmittance value. The experimental results show that the image processed by the proposed method has good contrast. The color saturation and authenticity are effectively maintained. And the detailed information of the mountain recorded by the image is better restored, which can provide a real data basis for slope monitoring.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLVIII-3-W1-2022/31/2022/isprs-archives-XLVIII-3-W1-2022-31-2022.pdf
spellingShingle X. L. Liu
T. Zhang
Y. H. Liu
R. J. Wang
A NEW METHOD FOR DEHAZING OF UAV REMOTE SENSING IMAGES BASED ON IMPROVED DARK CHANNEL PRIOR
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
title A NEW METHOD FOR DEHAZING OF UAV REMOTE SENSING IMAGES BASED ON IMPROVED DARK CHANNEL PRIOR
title_full A NEW METHOD FOR DEHAZING OF UAV REMOTE SENSING IMAGES BASED ON IMPROVED DARK CHANNEL PRIOR
title_fullStr A NEW METHOD FOR DEHAZING OF UAV REMOTE SENSING IMAGES BASED ON IMPROVED DARK CHANNEL PRIOR
title_full_unstemmed A NEW METHOD FOR DEHAZING OF UAV REMOTE SENSING IMAGES BASED ON IMPROVED DARK CHANNEL PRIOR
title_short A NEW METHOD FOR DEHAZING OF UAV REMOTE SENSING IMAGES BASED ON IMPROVED DARK CHANNEL PRIOR
title_sort new method for dehazing of uav remote sensing images based on improved dark channel prior
url https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLVIII-3-W1-2022/31/2022/isprs-archives-XLVIII-3-W1-2022-31-2022.pdf
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