Low-light image restoration using bright channel prior-based variational Retinex model

Abstract This paper presents a low-light image restoration method based on the variational Retinex model using the bright channel prior (BCP) and total-variation minimization. The proposed method first estimates the bright channel to control the amount of brightness enhancement. Next, the variationa...

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Main Authors: Seonhee Park, Byeongho Moon, Seungyong Ko, Soohwan Yu, Joonki Paik
Format: Article
Language:English
Published: SpringerOpen 2017-06-01
Series:EURASIP Journal on Image and Video Processing
Subjects:
Online Access:http://link.springer.com/article/10.1186/s13640-017-0192-3
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spelling doaj-639fb5a81521479d930b26dacd021cc32020-11-24T21:14:33ZengSpringerOpenEURASIP Journal on Image and Video Processing1687-52812017-06-012017111110.1186/s13640-017-0192-3Low-light image restoration using bright channel prior-based variational Retinex modelSeonhee Park0Byeongho Moon1Seungyong Ko2Soohwan Yu3Joonki Paik4The Graduate School of Advanced Imaging Science, Multimedia and Film, Chung-Ang, UniversityThe Graduate School of Advanced Imaging Science, Multimedia and Film, Chung-Ang, UniversityThe Graduate School of Advanced Imaging Science, Multimedia and Film, Chung-Ang, UniversityThe Graduate School of Advanced Imaging Science, Multimedia and Film, Chung-Ang, UniversityThe Graduate School of Advanced Imaging Science, Multimedia and Film, Chung-Ang, UniversityAbstract This paper presents a low-light image restoration method based on the variational Retinex model using the bright channel prior (BCP) and total-variation minimization. The proposed method first estimates the bright channel to control the amount of brightness enhancement. Next, the variational Retinex-based energy function is iteratively minimized to estimate the improved illumination and reflectance using the BCP. Contrast of the estimated illumination is enhanced using the gamma correction and histogram equalization to reduce a color distortion and noise amplification. Experimental results show that the proposed method can provide the better restored result than the existing methods without unnatural artifacts such as noise amplification and halo effects near edges.http://link.springer.com/article/10.1186/s13640-017-0192-3Low-light image enhancementRetinexBright channel prior
collection DOAJ
language English
format Article
sources DOAJ
author Seonhee Park
Byeongho Moon
Seungyong Ko
Soohwan Yu
Joonki Paik
spellingShingle Seonhee Park
Byeongho Moon
Seungyong Ko
Soohwan Yu
Joonki Paik
Low-light image restoration using bright channel prior-based variational Retinex model
EURASIP Journal on Image and Video Processing
Low-light image enhancement
Retinex
Bright channel prior
author_facet Seonhee Park
Byeongho Moon
Seungyong Ko
Soohwan Yu
Joonki Paik
author_sort Seonhee Park
title Low-light image restoration using bright channel prior-based variational Retinex model
title_short Low-light image restoration using bright channel prior-based variational Retinex model
title_full Low-light image restoration using bright channel prior-based variational Retinex model
title_fullStr Low-light image restoration using bright channel prior-based variational Retinex model
title_full_unstemmed Low-light image restoration using bright channel prior-based variational Retinex model
title_sort low-light image restoration using bright channel prior-based variational retinex model
publisher SpringerOpen
series EURASIP Journal on Image and Video Processing
issn 1687-5281
publishDate 2017-06-01
description Abstract This paper presents a low-light image restoration method based on the variational Retinex model using the bright channel prior (BCP) and total-variation minimization. The proposed method first estimates the bright channel to control the amount of brightness enhancement. Next, the variational Retinex-based energy function is iteratively minimized to estimate the improved illumination and reflectance using the BCP. Contrast of the estimated illumination is enhanced using the gamma correction and histogram equalization to reduce a color distortion and noise amplification. Experimental results show that the proposed method can provide the better restored result than the existing methods without unnatural artifacts such as noise amplification and halo effects near edges.
topic Low-light image enhancement
Retinex
Bright channel prior
url http://link.springer.com/article/10.1186/s13640-017-0192-3
work_keys_str_mv AT seonheepark lowlightimagerestorationusingbrightchannelpriorbasedvariationalretinexmodel
AT byeonghomoon lowlightimagerestorationusingbrightchannelpriorbasedvariationalretinexmodel
AT seungyongko lowlightimagerestorationusingbrightchannelpriorbasedvariationalretinexmodel
AT soohwanyu lowlightimagerestorationusingbrightchannelpriorbasedvariationalretinexmodel
AT joonkipaik lowlightimagerestorationusingbrightchannelpriorbasedvariationalretinexmodel
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