Image super-resolution using similarity
| Project/Area Number |
25420383
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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 |
Communication/Network engineering
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| Research Institution | Keio University |
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Principal Investigator |
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| Project Period (FY) |
2013-04-01 – 2016-03-31
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| Project Status |
Completed (Fiscal Year 2015)
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| Budget Amount *help |
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2015: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2014: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2013: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
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| Keywords | 超解像 / 画像補間 / 複数面フィッティング / ジャギー / 補間 / ショックフィルタ / 自己相似 / 非局所平均 / 辞書学習 |
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| Outline of Final Research Achievements |
In this research, we propose some fast and high performance super resolution methods from a single image. One method is based on the similarity of image. This makes a dictionary from random sampled patches from original and down-sampled images and apple L2 approximation to obtain a high resolution image. Another method is based on interpolation for high speed implementation. This utilize the bilateral weight of pixels in low resolution image as interpolation coefficient. With local interpolation coefficients, the high resolution images are obtained by applying direct interpolation of LR image. Through the simulations, the proposed methods are shown to be efficient for fast and high performance super resolution.
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Report
(4 results)
Research Products
(10 results)
