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论文类型：期刊论文

发表时间：2014-03-01

发表刊物：IEEE JOURNAL ON EMERGING AND SELECTED TOPICS IN CIRCUITS AND SYSTEMS

收录刊物：SCIE、EI、Scopus

卷号：4

期号：1

页面范围：70-81

ISSN号：2156-3357

关键字：Image retargeting; Laplacian regularization; shape parameter

摘要：We present a novel grid-based image retargeting approach that is able to balance important/unimportant contents while minimizing visual distortions on image geometric structures. Our approach begins with a structure-consistent importance map, efficiently obtained by filtering image saliency under the guidance of image gradients. Then we maintain the important contents located by the importance map, and more importantly balance the spatial distribution adaptively between the important/unimportant contents by globally optimizing a shape parameter to constrain scaling factors. Moreover, to preserve some geometric structures (e. g., straight lines and circles) which occupy multiple quads, a Laplacian regularization term is exploited to smoothly propagate distortions. Finally, all these constraints are cast into a quadratic programming, the global optima of which can be found efficiently. Both subjective and objective evaluations are conducted to show the effectiveness of our approach.