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内容感知图像缩放技术综述 被引量:12

Survey on content-aware image resizing techniques
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摘要 随着不同分辨率和纵横比的显示设备的迅猛增长,内容感知图像缩放技术逐渐成为图像处理领域新的研究热点之一。内容感知图像缩放的目标是在任意改变图像大小时保持图像中的主体特征不变。围绕其关键步骤:图像重要度识别和基于重要度的缩放,先概述重要度识别的相关方法,然后重点综述基于重要度的缩放技术。根据缩放是在像素级上操作还是亚像素级上操作,或者两者兼有,将其分为基于线裁剪缩放、基于图像变形缩放和多操作缩放3类,并比较各类方法的优缺点,同时给出各类方法所适合处理的图像类型。最后在分析各类研究方法的基础上,给出了内容感知缩放技术的可能发展方向。 With the rapid growth of the diversity and versatility of display devices which all come in different aspect ratios and resolutions, the content-aware image resizing has become one of the hot research fields in image processing. The main objective of such a technique is to preserve the image features when changing its size. The most content-aware image resizing methods have two basic steps: content significance recognition and image resizing based on a significance map. Firstly, the classic methods of the significance recognition are surveyed. Secondly, the resizing technologies based on significance maps are summarized. According to resizing methods based on pixel level discrete operating, sub-pixcl level continuous operation or combination of the discrete operating and continuous operation, it can be categorized into image resizing based on seam carving, image resizing based on warping or multi-operator resizing. Thirdly, the algorithm effect comparisons between classes are given and their suitable image types are presented. Finally, future directions are discussed.
作者 施美玲 徐丹
出处 《中国图象图形学报》 CSCD 北大核心 2012年第2期157-168,共12页 Journal of Image and Graphics
基金 国家自然科学基金项目(60663010) 高等学校博士学科点专项科研基金项目(20095301110006)
关键词 内容感知图像缩放 重要度图 显著度图 线裁剪 基于图像变形缩放 多操作缩放 content-aware image resizing importance map saliency map seam carving image warping multi-operation
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  • 1Chen LQ,Xie X,Fan X,Ma WY,Zhang HJ,Zhou HQ.A visual attention model for adapting images on small displays.Multimedia Systems,2003,9(4):353-364.[doi:10.1007/s00530-003-0105-4].
  • 2Wang Y,Li HQ,Liu ZK,Chen CW.Attention information based spatial adaptation framework for browsing videos via mobile devices.Advances in Multimedia Information Processing,2006,4621:788-797.[doi:10.1007/11922162_90].
  • 3Deselaers T,Dreuw P,Ney H.Pan,zoom,scan-time-coherent,trained automatic video cropping.In:Ahuja N,Shapiro L,eds.Proc.of the Int'l Conf.on Computer Vision and Pattern Recognition.Anchorage:IEEE Press,2008.1-8.[doi:10.1109/CVPR.2008.4587729].
  • 4Xie X,Liu H,Ma WY,Zhang HJ.Browsing large pictures under limited display sizes.IEEE Trans.on Multimedia,2006,8(4):707-715.[doi:10.1109/TMM.2006.876294].
  • 5Jiang SQ,Liu HY,Zhao Z,Huang QM,Gao W.Generating video sequence from photo image for mobile screens by content analysis.In:Gao W,ed.Proc.of the Int'l Conf.on Multimedia and Expo.Beijing:IEEE Press,2007.1475-1478.[doi:10.1109/ICME.2007.4284940].
  • 6Setlur V,Lechner T,Nienhaus M,Gooch B.Retargeting images and video for preserving information saliency.IEEE Computer Graphics and Applications,2007,27(5):80-88.[doi:10.1109/MCG.2007.133].
  • 7Rubinstein M,Shamir A,Avidan S.Improved seam carving for video retargeting.ACM Trans.on Graphics,2008,27(3):16.[doi:10.1145/1360612.1360615].
  • 8Huang H,Fu TN,Rosin PL,Qi C.Real-Time content-aware image resizing.Science in China Series F:Information Sciences,2009,52(2):172-182.[doi:10.1007/s11432-009-0041-9].
  • 9Wolf L,Guttmann M,Cohen-Or D.Non-Homogeneous content-driven video-retargeting.In:Davis L,Bouthemy P,Ikeuchi K,eds.Proc.of the Int'l Conf.on Computer Vision.Rio de Janeiro:IEEE Press,2007.1-6.[doi:10.1109/ICCV.2007.4409010].
  • 10Ren TW,Liu Y,Wu GS.Image retargeting based on global energy optimization.In:Lin CY,Cox I,eds.Proc.of the Int'l Conf.on Multimedia and Expo.New York:IEEE Press,2009.406-409.[doi:10.1109/ICME.2009.5202520].

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  • 1杨云峰,苏志勋,胡金燕.一种保持边缘特征的图像插值方法[J].中国图象图形学报,2005,10(10):1248-1251. 被引量:21
  • 2DeCarlo D, Santella A. Stylization and abstraction of photographs [ J]. ACM Transactions nn Graphics, 2002, 21 (3) :769-776. [DOI: 10. 1145/566654. 566650].
  • 3hti L, Koch C, Niebur E. A model of saliency-based visual attention tbr rapid scene analysis [ J ]. [EEE Transactions on Pattern Analysis and Machine Intelligence, 1998, 20 ( 11 ) : 1254-1259. [DOI: 10. 1109/34. 730558 ].
  • 4Shi M I,, Yang L, Peng G Q, et al. A content-aware image resi- zing me/hod with promhlen/ objec! size adjusted [ C l//The 17lh ACM Symposium on VRST. New York, USA: Assoeiation forComputing Machinery, 2010: 175-176.
  • 5'en F, Luan Q, Liang 1., et al. CoLor sketch generation [ C]// The 4th International Symposium on Non-Photorealistic Animaticm and Rendering. New York. USA: ACM, 2006:47-54. [ DOI: 10. 1145/1124"728. 1124737 ].
  • 6Zhao M, Zhu S C. Sisley the Abstract Painter [ C]// The 8lh International Symposium on NonPholorealistic Animation and Rendering. New York, USA: ACM, 2010: 99-107. IDOl: 10. ! 145/1809939. 1809951 ].
  • 7Cheng M M, Zhang G X, Milra N J, et al. Global contrast based salient region detection [ C ]//Proeeedings of IEEE CVPR 2011. Washington DC, LISA: IEEE Computer Society, 2011:409-416.
  • 8Tnmasi C, Manduchi R. Bilateral filtering fir gray and color ima- ges [ C ]//Proceedings of tie 6lh International Conference on Computer Vision. Bombay India: 1EEE Computer Society, 1998 : 839-846.
  • 9Comaniciu D, Meer P. Mean shift: a xbust apptvach toward fea- ture space analysis [J]. IEEE Transaetims on Pattern Analysis and Machine Intelligence, 2002, 24 ( 5 ) : 603-619. [ DOI: 10. 1109/34. 1000236].
  • 10Kuwahara M, Hachimura K, Eiho S, et al. Prc'essing of rian- giocardiographic images [ C ]//Digital Processing of Biomedical hnages. New York, USA: Plenum, 1976:187-202.

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