A Bayesian Framework for Single Image Dehazing considering Noise

The single image dehazing algorithms in existence can only satisfy the demand for dehazing efficiency, not for denoising. In order to solve the problem, a Bayesian framework for single image dehazing considering noise is proposed. Firstly, the Bayesian framework is transformed to meet the dehazing a...

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Detalles Bibliográficos
Autores principales: Nan, Dong, Bi, Du-yan, Liu, Chang, Ma, Shi-ping, He, Lin-yuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4152986/
https://www.ncbi.nlm.nih.gov/pubmed/25215327
http://dx.doi.org/10.1155/2014/651986
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author Nan, Dong
Bi, Du-yan
Liu, Chang
Ma, Shi-ping
He, Lin-yuan
author_facet Nan, Dong
Bi, Du-yan
Liu, Chang
Ma, Shi-ping
He, Lin-yuan
author_sort Nan, Dong
collection PubMed
description The single image dehazing algorithms in existence can only satisfy the demand for dehazing efficiency, not for denoising. In order to solve the problem, a Bayesian framework for single image dehazing considering noise is proposed. Firstly, the Bayesian framework is transformed to meet the dehazing algorithm. Then, the probability density function of the improved atmospheric scattering model is estimated by using the statistical prior and objective assumption of degraded image. Finally, the reflectance image is achieved by an iterative approach with feedback to reach the balance between dehazing and denoising. Experimental results demonstrate that the proposed method can remove haze and noise simultaneously and effectively.
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spelling pubmed-41529862014-09-11 A Bayesian Framework for Single Image Dehazing considering Noise Nan, Dong Bi, Du-yan Liu, Chang Ma, Shi-ping He, Lin-yuan ScientificWorldJournal Research Article The single image dehazing algorithms in existence can only satisfy the demand for dehazing efficiency, not for denoising. In order to solve the problem, a Bayesian framework for single image dehazing considering noise is proposed. Firstly, the Bayesian framework is transformed to meet the dehazing algorithm. Then, the probability density function of the improved atmospheric scattering model is estimated by using the statistical prior and objective assumption of degraded image. Finally, the reflectance image is achieved by an iterative approach with feedback to reach the balance between dehazing and denoising. Experimental results demonstrate that the proposed method can remove haze and noise simultaneously and effectively. Hindawi Publishing Corporation 2014 2014-08-19 /pmc/articles/PMC4152986/ /pubmed/25215327 http://dx.doi.org/10.1155/2014/651986 Text en Copyright © 2014 Dong Nan et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Nan, Dong
Bi, Du-yan
Liu, Chang
Ma, Shi-ping
He, Lin-yuan
A Bayesian Framework for Single Image Dehazing considering Noise
title A Bayesian Framework for Single Image Dehazing considering Noise
title_full A Bayesian Framework for Single Image Dehazing considering Noise
title_fullStr A Bayesian Framework for Single Image Dehazing considering Noise
title_full_unstemmed A Bayesian Framework for Single Image Dehazing considering Noise
title_short A Bayesian Framework for Single Image Dehazing considering Noise
title_sort bayesian framework for single image dehazing considering noise
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4152986/
https://www.ncbi.nlm.nih.gov/pubmed/25215327
http://dx.doi.org/10.1155/2014/651986
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