| Multi-task Gaussian Process Regression-based Image Super Resolution |
| Jiang XW(蒋心为); Xinwei Jiang
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| 2015-09
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会议名称 | British Machine Vision Conference (BMVC)
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会议录名称 | The British Machine Vision Association
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会议日期 | 2015.9.7-2015.9.10
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会议地点 | Swansea
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摘要 | This paper presents a novel framework for image super resolution (SR) based on the multi-task gaussian process (MTGP) regression. The core idea is to treat each pixel prediction using gaussian process regression as one single task and cast recovering a high resolution image patch as a multi-task learning problem. In contrast to prior Gaussian process regression-based SR approaches, our algorithm induces the inter-task correlation for considering image structures. We demonstrate the efficiency and effectiveness of the proposed method by applying it to the classic image dataset and experimental results show our approach is competitive with even outperforms the related and state-of-the-art methods. |
关键词 | Super Resolution
Multi-task Gaussian Process
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文献类型 | 会议论文
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条目标识符 | http://ir.ia.ac.cn/handle/173211/11964
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专题 | 综合信息系统研究中心
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通讯作者 | Xinwei Jiang |
作者单位 | Institute of Automation,Chinese Academy of Sciences
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推荐引用方式 GB/T 7714 |
Jiang XW,Xinwei Jiang. Multi-task Gaussian Process Regression-based Image Super Resolution[C],2015.
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文件名:
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504 bmvc_final.pdf
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格式:
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Adobe PDF
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