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...
Main Authors: | , , , , |
---|---|
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 |
id |
doaj-639fb5a81521479d930b26dacd021cc3 |
---|---|
record_format |
Article |
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 |
_version_ |
1716746766395637760 |