Probabilistic Image Processing based on Non-Linear Filter Theory
| Project/Area Number |
15K20870
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Perceptual information processing
Soft computing
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| Research Institution | Tohoku University |
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Principal Investigator |
Kataoka Shun 東北大学, 情報科学研究科, 助教 (50737278)
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| Research Collaborator |
YASUDA Muneki
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| Project Period (FY) |
2015-04-01 – 2018-03-31
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| Project Status |
Completed (Fiscal Year 2017)
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| Budget Amount *help |
¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
Fiscal Year 2017: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2016: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2015: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
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| Keywords | 確率的情報処理 / 画像処理 / マルコフ確率場 / 確率伝搬法 / 確率的画像処理 / Permutohedral Latice |
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| Outline of Final Research Achievements |
The purpose of this project was to propose the new probabilistic image processing method based on the non-linear filter theory. During this project, we proposed some probabilistic inference method such as the fast image processing method based on the non-linear filter theory. On the other hands, in this project, we could propose many information processing systems based on the latest inference frameworks such as quantum annealing and sparse modeling theory. These were new directions which were not considered in the original plan. We consider that our results of this project can contribute the development of the signal processing researches including the image processing.
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Report
(4 results)
Research Products
(23 results)
