Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/9540
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dc.contributor.authorKannan, R-
dc.contributor.authorGhinea, G-
dc.contributor.authorSwaminathan, S-
dc.date.accessioned2014-12-17T14:20:57Z-
dc.date.available2015-06-01-
dc.date.available2014-12-17T14:20:57Z-
dc.date.issued2015-
dc.identifier.citationIEEE Signal Processing Letters, 22 (6): pp. 686 - 690, 2015en_US
dc.identifier.issn1070-9908-
dc.identifier.urihttp://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6942143-
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/9540-
dc.description.abstractIn this letter, a novel salient region detection approach is proposed. Firstly, color contrast cue and color distribution cue are computed by exploiting patch level and region level image abstractions in a unified way, where these two cues are fused to compute an initial saliency map. A simple and computationally efficient adaptive saliency refinement approach is applied to suppress saliency of background noises, and to emphasize saliency of objects uniformly. Finally, the saliency map is computed by integrating the refined saliency map with center prior map. In order to compensate different needs in speed/accuracy tradeoff, three variants of the proposed approach are also presented in this letter. The experimental results on a large image dataset show that the proposed approach achieve the best performance over several state-of-the-art approaches.en_US
dc.languageeng-
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.subjectAdaptive saliency refinementen_US
dc.subjectCenter prioren_US
dc.subjectColor contrasten_US
dc.subjectColor distributionen_US
dc.subjectSaliency detectionen_US
dc.titleSalient region detection using patch level and region level image abstractionsen_US
dc.typeArticleen_US
dc.identifier.doihttp://dx.doi.org/10.1109/LSP.2014.2366192-
dc.relation.isPartOfIEEE Signal Processing Letters-
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