| Presentation | 2019-12-05 [Special Talk] Representation of moving-image's sparsity and its applications to adaptive moving-image restoration Takahiro Saito, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | This talk states that statistical sparsity of a moving-image sequence can be properly represented in the domain of the 3-D mean-separation-type short-time DFT (3-D MS2T-DFT). Moreover, taking account of the probability distribution of additive noise, this talk addresses the problem how to construct shrinkage functions, which are used to remove effects of the noise in the 3-D MS2T-DFT domain selectively, as the Bayes LS estimators, and demonstrates that the adaptive application of the shrinkage functions leads to the accomplishment of the state-of-the-art moving-image restoration in the restoration tasks of color moving-image denoising, Poisson-Gaussian color moving-image restoration, and single-plate color-mosaicked moving-image restoration. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Brain Neuroscience / Sparse Coding / Statistical Modeling / Signal Restoration / Moving-Image Processing |
| Paper # | CS2019-75,IE2019-55 |
| Date of Issue | 2019-11-28 (CS, IE) |
| Conference Information | |
| Committee | IE / CS / IPSJ-AVM / ITE-BCT |
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| Conference Date | 2019/12/5(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Aiina Center |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Image coding, Communications and streaming technologies, etc. |
| Chair | Hideaki Kimata(NTT) / Hidenori Nakazato(Waseda Univ.) / Sei Naito(KDDI Research, Inc.) / Kyoichi Saito(NHK) |
| Vice Chair | Kazuya Kodama(NII) / Keita Takahashi(Nagoya Univ.) / Jun Terada(NTT) / / Eichi Murata(Kyoto Univ.) / Tomomi Fukazawa(TBS) |
| Secretary | Kazuya Kodama(NTT) / Keita Takahashi(NHK) / Jun Terada(Waseda Univ.) / (Mitsubishi Electric) / Eichi Murata(NTT) / Tomomi Fukazawa(Tokyo Univ. of Science) |
| Assistant | Kyohei Unno(KDDI Research) / Norishige Fukushima(Nagoya Inst. of Tech.) / Kazutaka Hara(NTT) / Hiroyuki Saito(OKI) / / Minoru Okada(Nara Institute of Science and Technology) / Jun Yukawa(Mitsubishi Electric Corporation) / Takao Tsuda(NHK) |
| Paper Information | |
| Registration To | Technical Committee on Image Engineering / Technical Committee on Communication Systems / Special Interest Group on Audio Visual and Multimedia Information Processing / Technical Group on Broadcasting and Communication Technologies |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | [Special Talk] Representation of moving-image's sparsity and its applications to adaptive moving-image restoration |
| Sub Title (in English) | |
| Keyword(1) | Brain Neuroscience |
| Keyword(2) | Sparse Coding |
| Keyword(3) | Statistical Modeling |
| Keyword(4) | Signal Restoration |
| Keyword(5) | Moving-Image Processing |
| 1st Author's Name | Takahiro Saito |
| 1st Author's Affiliation | Kanagawa University(Kanagawa Univ.) |
| Date | 2019-12-05 |
| Paper # | CS2019-75,IE2019-55 |
| Volume (vol) | vol.119 |
| Number (no) | CS-323,IE-324 |
| Page | pp.pp.29-34(CS), pp.29-34(IE), |
| #Pages | 6 |
| Date of Issue | 2019-11-28 (CS, IE) |