广东海洋大学学报Issue(6)：82-86,5.
一种改进的图像视觉显著性检测算法
An Improved Visual Saliency Detection Algorithm
摘要
Abstract
Visual saliency detection plays an important role in image segmentation. It proposed a novel method for saliency detection. Firstly, the image is partitioned into a set of superpixels which can be viewed as nodes of a close-loop graph. Secondly, it computes the saliency values of these nodes via manifold ranking, and forms a saliency map corresponding to the image. Finally, the Sigmoid function correction is applied to the saliency map for suppressing the saliency values of background nodes and facilitating them of foreground nodes. Comparisons of experimental analysis for existing methods show that the proposed method can easily discriminate salient objects from background regions, and performs better in terms of robustness and performance.关键词
显著性检测/显著图/超像素/流形排名/Sigmoid函数Key words
Visual saliency detection/Saliency map/Superpixel/Manifold ranking/Sigmoid function分类
信息技术与安全科学引用本文复制引用
徐兵,李振德..一种改进的图像视觉显著性检测算法[J].广东海洋大学学报,2013,(6):82-86,5.基金项目
广东省2012年现代信息服务专项资金项目（GDEID2012IS071），广东海洋大学人才科研启动项目 （）
