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Paper Abstract and Keywords
Presentation 2020-02-27 13:30
Chromatic Aberration Correction of Color Images Using Deep Learning with Each Channel Training Based on Contrast Enhancement
Naoto Nagashima, Mitsuhiko Meguro (Nihon Univ.) ITS2019-35 IE2019-73
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we propose a new correcting method of chromatic aberration occurring in color images using Deep Learning. In this proposed method, the existing Deep Learning for denoising (well known as DnCNN) is used for chromatic aberration correction purpose. In a lens optical system for imaging, the wavelength of $G$ is designed to be in focus. Therefore, light $R$ with longer wavelength than $G$ and light $B$ with shorter wavelength are out of focus and may cause chromatic aberration. We propose a method to remove the deterioration of chromatic aberration of $R$ channel and $B$ channel by using the $G$ channel without chromatic aberration. In the case of learning DnCNN for restoration of $R$, it is better to perform correction with CNN learned using only learning data of $R$ and $G$. Moreover, for restoration $B$ channel, it is better using $B$ and $G$ data only than using all $RGB$ data. By separating the two DnCNN networks to be trained for the $R$ or $B$ channels, an accuracy and an efficiency of DnCNN can be improved. Further, the training and correcting process by using the $G$ channel with enhanced contrast, make clear the criteria for $R$ and $B$ channel edge correction. Through experimental results, we show the effectiveness of our proposed method
Keyword (in Japanese) (See Japanese page) 
(in English) chromatic aberration / Deep Learning / color channel / color image / contrast enhancement / / /  
Reference Info. IEICE Tech. Rep., vol. 119, no. 422, IE2019-73, pp. 183-188, Feb. 2020.
Paper # IE2019-73 
Date of Issue 2020-02-20 (ITS, IE) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
Copyright
and
reproduction
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF ITS2019-35 IE2019-73

Conference Information
Committee ITE-HI IE ITS ITE-MMS ITE-ME ITE-AIT  
Conference Date 2020-02-27 - 2020-02-28 
Place (in Japanese) (See Japanese page) 
Place (in English) Hokkaido Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Image Processing, etc. 
Paper Information
Registration To IE 
Conference Code 2020-02-HI-IE-ITS-MMS-ME-AIT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Chromatic Aberration Correction of Color Images Using Deep Learning with Each Channel Training Based on Contrast Enhancement 
Sub Title (in English)  
Keyword(1) chromatic aberration  
Keyword(2) Deep Learning  
Keyword(3) color channel  
Keyword(4) color image  
Keyword(5) contrast enhancement  
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1st Author's Name Naoto Nagashima  
1st Author's Affiliation Nihon University (Nihon Univ.)
2nd Author's Name Mitsuhiko Meguro  
2nd Author's Affiliation Nihon University (Nihon Univ.)
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Speaker
Date Time 2020-02-27 13:30:00 
Presentation Time 15 
Registration for IE 
Paper # IEICE-ITS2019-35,IEICE-IE2019-73 
Volume (vol) IEICE-119 
Number (no) no.421(ITS), no.422(IE) 
Page pp.183-188 
#Pages IEICE-6 
Date of Issue IEICE-ITS-2020-02-20,IEICE-IE-2020-02-20 


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