Multi-task Gaussian Process Regression-based Image Super Resolution

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	Multi-task Gaussian Process Regression-based Image Super Resolution
	Jiang XW(蒋心为); Xinwei Jiang
	2015-09
会议名称	British Machine Vision Conference (BMVC)
会议录名称	The British Machine Vision Association
会议日期	2015.9.7-2015.9.10
会议地点	Swansea
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
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/11964
专题	综合信息系统研究中心
通讯作者	Xinwei Jiang
作者单位	Institute of Automation,Chinese Academy of Sciences
推荐引用方式 GB/T 7714	Jiang XW,Xinwei Jiang. Multi-task Gaussian Process Regression-based Image Super Resolution[C],2015.