Robust super-resolution method for depth images based on image colorization
| Project/Area Number |
15K00246
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Perceptual information processing
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| Research Institution | Kogakuin University |
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Principal Investigator |
KONISHI KATSUMI 工学院大学, 情報学部(情報工学部), 准教授 (20339138)
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| Co-Investigator(Kenkyū-buntansha) |
古川 利博 東京理科大学, 工学部情報工学科, 教授 (00190140)
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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: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2016: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2015: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Keywords | 画像復元 / 画像修復 / 最適化 / 深度画像 / カラリゼーション / 画像処理 |
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| Outline of Final Research Achievements |
This work proposed a new depth image recovery method based on image colorization. Assuming that neighbor pixels of a depth image have almost the same values when neighbor pixels of a chrominance image have almost the same values, the depth image recovery problem was formulated as the mixed l_1 and l_2 minimization problem and provides an iterative algorithm. Numerical examples show the efficiency of the proposed algorithm.
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Report
(4 results)
Research Products
(8 results)
