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Proceedings Paper

A local correlation based visual saliency model
Author(s): Yang Li; Xuanqin Mou
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Paper Abstract

We propose a novel local correlation based saliency model that is friendly to application of video coding. The proposed model is developed in YCbCr color space. We extract feature maps with local mean and local contrast of each channel image and its Gaussian blurred image, and produce rarity maps by calculating the correlation between the feature maps of the original and blurred channels. The proposed saliency map is produced by a combination of the local mean rarity maps and the local contrast rarity maps across all the channels. Experiments validate that the proposed model works with excellent performance.

Paper Details

Date Published: 28 September 2016
PDF: 11 pages
Proc. SPIE 9971, Applications of Digital Image Processing XXXIX, 99712W (28 September 2016); doi: 10.1117/12.2236817
Show Author Affiliations
Yang Li, Xi'an Jiaotong Univ. (China)
Xuanqin Mou, Xi'an Jiaotong Univ. (China)


Published in SPIE Proceedings Vol. 9971:
Applications of Digital Image Processing XXXIX
Andrew G. Tescher, Editor(s)

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