High quality image resizing

doi:10.1016/j.neucom.2013.09.032

OPT OpenIR > 光谱成像技术研究室

	High quality image resizing
	Wang, Qi 1; Yuan, Yuan2
作者部门	光学影像学习与分析中心
	2014-05-05
发表期刊	NEUROCOMPUTING
ISSN	0925-2312
卷号	131 页码:348-356
摘要	An increasing amount of display devices with fixed sizes call for an adaptive strategy for optimal display. For this purpose, content aware image resizing techniques are developed. Previous works mainly lay their attention on the shrinkage operation of the examined image. Less efforts are paid on the expansion manipulation. Though some literatures claim an extension of their shrinkage operation to expanding the image in a similar way, the obtained results are not satisfying. In this paper, a high quality image resizing method is proposed to retain the details when stretching an image. Instead of using interpolation based techniques which are taken for granted by existing methods, an expansion model is first learned from a set of training images. Then the future enlargement is based on this principle. Experiments on two publicly available datasets demonstrate the effectiveness of the presented method. A further extension on video enlargement is also presented as an example. Though the proposed method is formulated in the context of seam carving, it can be readily extended to other techniques such as cropping, segmentation and warping based resizing methods. (C) 2014 Published by Elsevier B.V.
文章类型	Article
关键词	Image Resizing Saliency Dictionary Learning
WOS标题词	Science & Technology ; Technology
DOI	10.1016/j.neucom.2013.09.032
收录类别	SCI ; EI
关键词[WOS]	SALIENT REGION DETECTION ; VISUAL SALIENCY ; ADAPTIVE IMAGE ; SUPERRESOLUTION ; CONTRAST
语种	英语
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000332805700036
引用统计	被引频次：16[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.opt.ac.cn/handle/181661/22404
专题	光谱成像技术研究室
作者单位	1.Northwestern Polytech Univ, Xian 710072, Shaanxi, Peoples R China 2.Chinese Acad Sci, Ctr Opt IMagely Anal & Learning OPTIMAL, State Key Lab Transient Opt & Photon, Xian Inst Opt & Precis Mech, Xian 710119, Shaanxi, Peoples R China
推荐引用方式 GB/T 7714	Wang, Qi,Yuan, Yuan. High quality image resizing[J]. NEUROCOMPUTING,2014,131:348-356.
APA	Wang, Qi,&Yuan, Yuan.(2014).High quality image resizing.NEUROCOMPUTING,131,348-356.
MLA	Wang, Qi,et al."High quality image resizing".NEUROCOMPUTING 131(2014):348-356.

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文件名称/大小	文献类型	版本类型	开放类型	使用许可
High quality image r（2152KB）	期刊论文	出版稿	限制开放	CC BY	请求全文