@inproceedings{1e786f8dd1c849b9aa1b3c35b7928101,
title = "A local correlation based visual saliency model",
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.",
keywords = "Local correlation, Saliency detection, Video coding",
author = "Yang Li and Xuanqin Mou",
note = "Publisher Copyright: {\textcopyright} 2016 SPIE.; Applications of Digital Image Processing XXXIX ; Conference date: 29-08-2016 Through 01-09-2016",
year = "2016",
doi = "10.1117/12.2236817",
language = "英语",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Tescher, \{Andrew G.\}",
booktitle = "Applications of Digital Image Processing XXXIX",
}