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Journal of Zhejiang University SCIENCE C 2014 Vol.15 No.9 P.697-716

http://doi.org/10.1631/jzus.C1400102


A survey for image resizing


Author(s):  Xiao Lin, Ying-lan Ma, Li-zhuang Ma, Rui-ling Zhang

Affiliation(s):  Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China; more

Corresponding email(s):   lin6008@126.com, lin6008@sjtu.edu.cn, ma-lz@cs.sjtu.edu.cn

Key Words:  Image resizing, Saliency measures, Cropping, Seam carving, Warping


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Xiao Lin, Ying-lan Ma, Li-zhuang Ma, Rui-ling Zhang. A survey for image resizing[J]. Journal of Zhejiang University Science C, 2014, 15(9): 697-716.

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publisher="Zhejiang University Press & Springer",
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Abstract: 
image resizing is a key technique for displaying images on different devices, and has attracted much attention in the past few years. This paper reviews the image resizing methods proposed in recent years, gives a detailed comparison on their performance, and reveals the main challenges raised in several important issues such as preserving an important region, minimizing distortions, and improving efficiency. Furthermore, this paper discusses the research trends and points out the possible hotspots in this field. We believe this survey can give some guidance for researchers from relevant research areas, offering them an overall and novel view.

图像缩放方法综述

研究目的:对图像缩放方法进行全面总结,为今后图像缩放研究提供新视角。
文章内容:通过对重要区域保持、最小化变形和性能方面的分析,总结各种图像缩放方法的优缺点。首先,分析了图像显著性检测方法。其次,将图像缩放方法分为缩放、裁剪、缝裁剪、变形、多算子和其他方法,总结了近年提出的一些视频缩放方法。最后,总结图像缩放方法,指出未来研究热点包括:基于视频显著性的视频缩放技术的深入研究,具有更多语义信息、复杂结构和不同拓扑关系的图像缩放方法的研究,对特殊场景图像的缩放,如何更加高效地进行图像缩放,等。
图像缩放;显著性检测;裁剪;缝裁剪;变形

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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