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摘要:
Salient detection approaches mainly use single local cues or global cues as its inputs features to detect salient objects,which are sensitive to complex background,so the effect of detection were not satisfactory.In this paper,we investigate the traits of saliency detection and observed the two following facts:Firstly,high-level saliency cues achieve better saliency detection results than low-level saliency cues.Secondly,multi-difference cues achieve better saliency detection results than single difference cues.Based on deeply analysis,we proposed an image saliency detection algorithm through high level multi-difference cues(HMDS).By using multi-difference,not only HMDS could remove the non-salient region effectively,but also it could enhance the pixel value of salient region at the same time.In order to evaluate the performance of HMDS,the proposed method is compared with seven state-of-the-art algorithms on five popular datasets.The final experimental results show that the proposed method performs effectiveness,and will have a perfect application prospect.
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篇名 High-Level Multi-difference Cues for Image Saliency Detection
来源期刊 国际计算机前沿大会会议论文集 学科 社会科学
关键词 HIGH-LEVEL SALIENCY detection Multi-difference SALIENCY map Salient region
年,卷(期) 2017,(1) 所属期刊栏目
研究方向 页码范围 129-131
页数 3页 分类号 C5
字数 语种
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研究主题发展历程
节点文献
HIGH-LEVEL
SALIENCY
detection
Multi-difference
SALIENCY
map
Salient
region
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引文网络交叉学科
相关学者/机构
期刊影响力
国际计算机前沿大会会议论文集
半年刊
北京市海淀区西三旗昌临801号
出版文献量(篇)
616
总下载数(次)
6
总被引数(次)
0
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