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	Single Image Super-Resolution via Iterative Collaborative Representation
	Zhang, Yulun ; Zhang, Yongbing ; Zhang, Jian ; Wang, Haoqian ; Dai, Qionghai
	2015
关键词	Iterative collaborative representation Super-resolution QUALITY
英文摘要	We propose a new model called iterative collaborative representation (ICR) for image super-resolution (SR). Most of popular SR approaches extract low-resolution (LR) features from the given LR image directly to recover its corresponding high-resolution (HR) features. However, they neglect to utilize the reconstructed HR image for further image SR enhancement. Based on this observation, we extract features from the reconstructed HR image to progressively upscale LR image in an iterative way. In the learning phase, we use the reconstructed and the original HR images as inputs to train the mapping models. These mapping models are then used to upscale the original LR images. In the reconstruction phase, mapping models and LR features extracted from the LR and reconstructed image are then used to conduct image SR in each iteration. Experimental results on standard images demonstrate that our ICR obtains state-of-the-art SR performance quantitatively and visually, surpassing recently published leading SR methods.; EI; CPCI-S(ISTP); zhangy114@mails.tsinghua.edu.cn; 63-73; 9315
语种	英语
出处	ADVANCES IN MULTIMEDIA INFORMATION PROCESSING - PCM 2015, PT II
DOI标识	10.1007/978-3-319-24078-7_7
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/436997]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Zhang, Yulun,Zhang, Yongbing,Zhang, Jian,et al. Single Image Super-Resolution via Iterative Collaborative Representation. 2015-01-01.

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