| Presentation | 2010/6/11 Hierarchical Lossless Image Coding Using Cellular Neural Network Seiya TAKENOUCHI, Hisashi AOMORI, Tsuyoshi OTAKE, Mamoru TANAKA, Ichiro MATSUDA, Susumu ITOH, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In this paper, a hierarchical lossless image coding scheme using cellular neural network (CNN) is proposed. The coding architecture of the proposed method is based on the lifting scheme that is one of the scalable coding architecture for still images, and the coding performance strongly depends on the prediction ability. To deal with this characteristic, an image interpolation is modeled by an optimal problem that minimizes the prediction error. By the high optimal ability of CNN, the optimal interpolated image can be obtained. Also, in order to achieve the high accuracy prediction, the parameters of CNN predictors are adjusted to the local structure of the image. In the coding layer, the arithmetic coder with context modeling is used for obtaining a high coding efficiency. Experimental results in various standard test images suggest that the coding performance of our proposed method is better than that of conventional hierarchical coding schemes. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | discrete-time cellular neural network / hierarchical coding / context modeling |
| Paper # | NC2010-11,NLP2010-11 |
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| Conference Information | |
| Committee | NC |
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| Conference Date | 2010/6/11(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Neurocomputing (NC) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Hierarchical Lossless Image Coding Using Cellular Neural Network |
| Sub Title (in English) | |
| Keyword(1) | discrete-time cellular neural network |
| Keyword(2) | hierarchical coding |
| Keyword(3) | context modeling |
| 1st Author's Name | Seiya TAKENOUCHI |
| 1st Author's Affiliation | Department of Electrical Engineering, Tokyo University of Science() |
| 2nd Author's Name | Hisashi AOMORI |
| 2nd Author's Affiliation | Department of Electrical Engineering, Tokyo University of Science |
| 3rd Author's Name | Tsuyoshi OTAKE |
| 3rd Author's Affiliation | Department of Software Science, Tamagawa University |
| 4th Author's Name | Mamoru TANAKA |
| 4th Author's Affiliation | Department of Electrical and Electronics Engineering, Sophia University |
| 5th Author's Name | Ichiro MATSUDA |
| 5th Author's Affiliation | Department of Electrical Engineering, Tokyo University of Science |
| 6th Author's Name | Susumu ITOH |
| 6th Author's Affiliation | Department of Electrical Engineering, Tokyo University of Science |
| Date | 2010/6/11 |
| Paper # | NC2010-11,NLP2010-11 |
| Volume (vol) | vol.110 |
| Number (no) | 83 |
| Page | pp.pp.- |
| #Pages | 5 |
| Date of Issue | |