ITE Technical Group Submission System
Conference Paper's Information
Online Proceedings
[Sign in]
 Go Top Page Go Previous   [Japanese] / [English] 

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.)
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. ITE Tech. Rep.
Paper #  
Date of Issue  
ISSN Print edition: ISSN 1342-6893  Online edition: ISSN 2424-1970
Download PDF

Conference Information
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 IEICE-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  
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.)
3rd Author's Name  
3rd Author's Affiliation ()
4th Author's Name  
4th Author's Affiliation ()
5th Author's Name  
5th Author's Affiliation ()
6th Author's Name  
6th Author's Affiliation ()
7th Author's Name  
7th Author's Affiliation ()
8th Author's Name  
8th Author's Affiliation ()
9th Author's Name  
9th Author's Affiliation ()
10th Author's Name  
10th Author's Affiliation ()
11th Author's Name  
11th Author's Affiliation ()
12th Author's Name  
12th Author's Affiliation ()
13th Author's Name  
13th Author's Affiliation ()
14th Author's Name  
14th Author's Affiliation ()
15th Author's Name  
15th Author's Affiliation ()
16th Author's Name  
16th Author's Affiliation ()
17th Author's Name  
17th Author's Affiliation ()
18th Author's Name  
18th Author's Affiliation ()
19th Author's Name  
19th Author's Affiliation ()
20th Author's Name  
20th Author's Affiliation ()
Date Time 2020-02-27 13:30:00 
Presentation Time 15 
Registration for IEICE-IE 
Paper #  
Volume (vol) ITE-44 
Number (no)  
#Pages ITE- 
Date of Issue  

[Return to Top Page]

[Return to ITE Web Page]

The Institute of Image Information and Television Engineers (ITE), Japan