Parametric Analytical Modulation Transfer Function Model in Turbid Atmosphere with Application to Image Restoration

To address the issues of image blurring and color distortion in hazy conditions, an image restoration method based on a parametric analytical modulation transfer function model is proposed under turbid atmospheric conditions. A source database is established using a numerical radiative transfer meth...

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Main Authors: Mengxing Guo, Pengfei Wu, Zizhao Fan, Hao Lu, Ruizhong Rao
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/16/21/3998
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author Mengxing Guo
Pengfei Wu
Zizhao Fan
Hao Lu
Ruizhong Rao
author_facet Mengxing Guo
Pengfei Wu
Zizhao Fan
Hao Lu
Ruizhong Rao
author_sort Mengxing Guo
collection DOAJ
description To address the issues of image blurring and color distortion in hazy conditions, an image restoration method based on a parametric analytical modulation transfer function model is proposed under turbid atmospheric conditions. A source database is established using a numerical radiative transfer method based on discrete ordinate. Through multivariate nonlinear fitting and linear interpolation, the quantitative relationships among critical spatial frequency, turbid atmospheric MTF, and key atmospheric optical parameters—such as optical thickness, single scattering albedo, and asymmetry factor—are examined. A fast and efficient parametric analytical MTF model for turbid atmospheres is developed and applied to restore images affected by fog. The results demonstrate that, within the applicable range of the model, the model’s maximum mean relative error and the root mean square error are 7.16% and 0.0454, respectively. The computational speed is nearly a thousand times faster than that of the numerical radiative transfer method, achieving high accuracy and ease of application. Images restored using this model exhibit enhanced clarity and quality, effectively compensating for the degradation in image quality caused by turbid atmospheres. This approach represents a novel solution to the challenges of image processing in complex atmospheric environments.
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spelling doaj-art-2da2a6e30f9040adbbb61b35fcd18ede2024-11-08T14:40:26ZengMDPI AGRemote Sensing2072-42922024-10-011621399810.3390/rs16213998Parametric Analytical Modulation Transfer Function Model in Turbid Atmosphere with Application to Image RestorationMengxing Guo0Pengfei Wu1Zizhao Fan2Hao Lu3Ruizhong Rao4Key Laboratory of Atmospheric Optics, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, ChinaKey Laboratory of Atmospheric Optics, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, ChinaKey Laboratory of Atmospheric Optics, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, ChinaKey Laboratory of Atmospheric Optics, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, ChinaKey Laboratory of Atmospheric Optics, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, ChinaTo address the issues of image blurring and color distortion in hazy conditions, an image restoration method based on a parametric analytical modulation transfer function model is proposed under turbid atmospheric conditions. A source database is established using a numerical radiative transfer method based on discrete ordinate. Through multivariate nonlinear fitting and linear interpolation, the quantitative relationships among critical spatial frequency, turbid atmospheric MTF, and key atmospheric optical parameters—such as optical thickness, single scattering albedo, and asymmetry factor—are examined. A fast and efficient parametric analytical MTF model for turbid atmospheres is developed and applied to restore images affected by fog. The results demonstrate that, within the applicable range of the model, the model’s maximum mean relative error and the root mean square error are 7.16% and 0.0454, respectively. The computational speed is nearly a thousand times faster than that of the numerical radiative transfer method, achieving high accuracy and ease of application. Images restored using this model exhibit enhanced clarity and quality, effectively compensating for the degradation in image quality caused by turbid atmospheres. This approach represents a novel solution to the challenges of image processing in complex atmospheric environments.https://www.mdpi.com/2072-4292/16/21/3998atmospheric opticsradiative transfermodulation transfer functionimage processingimaging through turbid media
spellingShingle Mengxing Guo
Pengfei Wu
Zizhao Fan
Hao Lu
Ruizhong Rao
Parametric Analytical Modulation Transfer Function Model in Turbid Atmosphere with Application to Image Restoration
Remote Sensing
atmospheric optics
radiative transfer
modulation transfer function
image processing
imaging through turbid media
title Parametric Analytical Modulation Transfer Function Model in Turbid Atmosphere with Application to Image Restoration
title_full Parametric Analytical Modulation Transfer Function Model in Turbid Atmosphere with Application to Image Restoration
title_fullStr Parametric Analytical Modulation Transfer Function Model in Turbid Atmosphere with Application to Image Restoration
title_full_unstemmed Parametric Analytical Modulation Transfer Function Model in Turbid Atmosphere with Application to Image Restoration
title_short Parametric Analytical Modulation Transfer Function Model in Turbid Atmosphere with Application to Image Restoration
title_sort parametric analytical modulation transfer function model in turbid atmosphere with application to image restoration
topic atmospheric optics
radiative transfer
modulation transfer function
image processing
imaging through turbid media
url https://www.mdpi.com/2072-4292/16/21/3998
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AT zizhaofan parametricanalyticalmodulationtransferfunctionmodelinturbidatmospherewithapplicationtoimagerestoration
AT haolu parametricanalyticalmodulationtransferfunctionmodelinturbidatmospherewithapplicationtoimagerestoration
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