| Presentation | 2020-02-27 Chromatic Aberration Correction of Color Images Using Deep Learning with Each Channel Training Based on Contrast Enhancement Naoto Nagashima, Mitsuhiko Meguro, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(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) |
| Keyword(in English) | chromatic aberration / Deep Learning / color channel / color image / contrast enhancement |
| Paper # | ITS2019-35,IE2019-73 |
| Date of Issue | 2020-02-20 (ITS, IE) |
| Conference Information | |
| Committee | ITE-HI / IE / ITS / ITE-MMS / ITE-ME / ITE-AIT |
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| Conference Date | 2020/2/27(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Hokkaido Univ. |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Image Processing, etc. |
| Chair | Takehiro Nagai(Tokyo Inst. of Tech.) / / / Norihiko Ishii(NHK) / Norio Tagawa(Tokyo Metropolitan Univ.) / Nobuhiko Mukai(Tokyo Cisy Univ.) |
| Vice Chair | / / / / Hiroyuki Arai(Nippon Institute of Technology) / Hisaki Nate(Tokyo Polytechnic Univ.) |
| Secretary | (NTT) / / / (Fukuoka Univ.) / Hiroyuki Arai(NHK) / Hisaki Nate(NHK) |
| Assistant | |
| Paper Information | |
| Registration To | Technical Group on Human Inormation / Technical Committee on Image Engineering / Technical Committee on Intelligent Transport Systems Technology / Technical Group on Multi-media Storage / Technical Group on Media Engineering / Technical Group on Artistic Image Technology |
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| Language | JPN |
| 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.) |
| Date | 2020-02-27 |
| Paper # | ITS2019-35,IE2019-73 |
| Volume (vol) | vol.119 |
| Number (no) | ITS-421,IE-422 |
| Page | pp.pp.183-188(ITS), pp.183-188(IE), |
| #Pages | 6 |
| Date of Issue | 2020-02-20 (ITS, IE) |