| Presentation | 2018-12-07 Chromatic Aberration Correction of Color Images Using Deep Neural Network for Each Channel Processing Naoto Nagashima, Mitsuhiko Meguro, |
|---|---|
| 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. DnCNN needs to be trained with both chromatic aberration images and original images not including these aberrations. 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. 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 processing |
| Paper # | SIS2018-33 |
| Date of Issue | 2018-11-29 (SIS) |
| Conference Information | |
| Committee | SIS |
|---|---|
| Conference Date | 2018/12/6(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Hagi Civic Center |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Smart Personal Systems, etc. |
| Chair | Takayuki Nakachi(NTT) |
| Vice Chair | Noriaki Suetake(Yamaguchi Univ.) / Tomoaki Kimura(Kanagawa Inst. of Tech.) |
| Secretary | Noriaki Suetake(Kyushu Inst. of Tech.) / Tomoaki Kimura(Tokyo Metropolitan Univ.) |
| Assistant | Takanori Koga(National Inst. of Tech. Tokuyama College) / Hideaki Misawa(National Inst. of Tech., Ube College) |
| Paper Information | |
| Registration To | Technical Committee on Smart Info-Media Systems |
|---|---|
| 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 Neural Network for Each Channel Processing |
| Sub Title (in English) | |
| Keyword(1) | chromatic aberration |
| Keyword(2) | Deep Learning |
| Keyword(3) | color channel |
| Keyword(4) | color image processing |
| 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 | 2018-12-07 |
| Paper # | SIS2018-33 |
| Volume (vol) | vol.118 |
| Number (no) | SIS-346 |
| Page | pp.pp.61-66(SIS), |
| #Pages | 6 |
| Date of Issue | 2018-11-29 (SIS) |