| Presentation | 2012-11-07 Bayesian image super-resolution of large image with a compound MRF and estimating registration parameters Toshiki KINOSHITA, Seiji MIYOSHI, |
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| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Super-resolution is a technique to estimate a higher resolution image from low-resolution images. In this manuscript, we first conduct processing large images in Bayesian super-resolution using latent variables of the line process by Kanemura et al. It is shown that we can obtain good results for a large image. Second, we propose a method of estimating registration parameters from any area of images. Previously, we estimated registration parameters from center area of images. This change allowed good estimation of registration parameters by using area which has a large change of pixel values. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | super-resolution / compound Markov random field prior / Bayesian inference / variational EM algorithm |
| Paper # | IBISML2012-35 |
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| Conference Information | |
| Committee | IBISML |
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| Conference Date | 2012/10/31(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Information-Based Induction Sciences and Machine Learning (IBISML) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Bayesian image super-resolution of large image with a compound MRF and estimating registration parameters |
| Sub Title (in English) | |
| Keyword(1) | super-resolution |
| Keyword(2) | compound Markov random field prior |
| Keyword(3) | Bayesian inference |
| Keyword(4) | variational EM algorithm |
| 1st Author's Name | Toshiki KINOSHITA |
| 1st Author's Affiliation | Graduate School of Science and Engineering, Kansai University() |
| 2nd Author's Name | Seiji MIYOSHI |
| 2nd Author's Affiliation | Faculty of Engineering Science, Kansai University |
| Date | 2012-11-07 |
| Paper # | IBISML2012-35 |
| Volume (vol) | vol.112 |
| Number (no) | 279 |
| Page | pp.pp.- |
| #Pages | 8 |
| Date of Issue | |