Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/9540
Title: Salient region detection using patch level and region level image abstractions
Authors: Kannan, R
Ghinea, G
Swaminathan, S
Keywords: Adaptive saliency refinement;Center prior;Color contrast;Color distribution;Saliency detection
Issue Date: 2015
Publisher: Institute of Electrical and Electronics Engineers Inc.
Citation: IEEE Signal Processing Letters, 22 (6): pp. 686 - 690, 2015
Abstract: In 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.
URI: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6942143
http://bura.brunel.ac.uk/handle/2438/9540
DOI: http://dx.doi.org/10.1109/LSP.2014.2366192
ISSN: 1070-9908
Appears in Collections:Dept of Computer Science Research Papers

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