PSYCH OpenIR  > 脑与认知科学国家重点实验室
Image Retargeting Quality Assessment
Liu, Yong-Jin1; Luo, Xi1; Xuan, Yu-Ming2; Chen, Wen-Feng2; Fu, Xiao-Lan2; Liu, YJ (reprint author), Tsinghua Univ, TNList, Dept Comp Sci & Technol, Beijing, Peoples R China.
2011
Source PublicationCOMPUTER GRAPHICS FORUM
ISSN0167-7055
SubtypeArticle
Volume30Issue:2Pages:583-592
Contribution Rank2
AbstractContent-aware image retargeting is a technique that can flexibly display images with different aspect ratios and simultaneously preserve salient regions in images. Recently many image retargeting techniques have been proposed. To compare image quality by different retargeting methods fast and reliably, an objective metric simulating the human vision system (HVS) is presented in this paper. Different from traditional objective assessment methods that work in bottom-up manner (i.e., assembling pixel-level features in a local-to-global way), in this paper we propose to use a reverse order (top-down manner) that organizes image features from global to local viewpoints, leading to a new objective assessment metric for retargeted images. A scale-space matching method is designed to facilitate extraction of global geometric structures from retargeted images. By traversing the scale space from coarse to fine levels, local pixel correspondence is also established. The objective assessment metric is then based on both global geometric structures and local pixel correspondence. To evaluate color images, CIE L*a*b* color space is utilized. Experimental results are obtained to measure the performance of objective assessments with the proposed metric. The results show good consistency between the proposed objective metric and subjective assessment by human observers.
Subject AreaPsychology Of Journalism
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Indexed BySCI
Language英语
Funding OrganizationNational Science Foundation of China [60970099] ; National Basic Research Program of China [2011CB302201] ; Tsinghua University [20101081863]
Project Intro.The authors thank the reviewers for their comments that help improve this paper. The program of PatchMatch, ShiftMap and the RetargetMe benchmark are taken from original publication websites. The authors thank Mr. G.X. Zhang for implementing other retargeting methods in Experiment 3. This work was supported by the National Science Foundation of China (Project 60970099), the National Basic Research Program of China 2011CB302201 and Tsinghua University Initiative Scientific Research Program 20101081863.
WOS IDWOS:000289996100036
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Document Type期刊论文
Identifierhttp://ir.psych.ac.cn/handle/311026/12849
Collection脑与认知科学国家重点实验室
Corresponding AuthorLiu, YJ (reprint author), Tsinghua Univ, TNList, Dept Comp Sci & Technol, Beijing, Peoples R China.
Affiliation1.Tsinghua Univ, TNList, Dept Comp Sci & Technol, Beijing, Peoples R China
2.Chinese Acad Sci, Inst Psychol, State Key Lab Brain & Cognit Sci, Beijing 100864, Peoples R China
Recommended Citation
GB/T 7714
Liu, Yong-Jin,Luo, Xi,Xuan, Yu-Ming,et al. Image Retargeting Quality Assessment[J]. COMPUTER GRAPHICS FORUM,2011,30(2):583-592.
APA Liu, Yong-Jin,Luo, Xi,Xuan, Yu-Ming,Chen, Wen-Feng,Fu, Xiao-Lan,&Liu, YJ .(2011).Image Retargeting Quality Assessment.COMPUTER GRAPHICS FORUM,30(2),583-592.
MLA Liu, Yong-Jin,et al."Image Retargeting Quality Assessment".COMPUTER GRAPHICS FORUM 30.2(2011):583-592.
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