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作 者:Jianwei Sun Junfeng Wu Hong Yu Meiling Zhang Qiang Luo Juanjuan Sun
机构地区:[1]College of Information Engineering,Dalian Ocean University,Dalian 116023,China [2]Key Laboratory of Marine Information Technology of Liaoning Province,Dalian 116023,China
出 处:《国际计算机前沿大会会议论文集》2017年第1期129-131,共3页International Conference of Pioneering Computer Scientists, Engineers and Educators(ICPCSEE)
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.
关 键 词:HIGH-LEVEL SALIENCY detection Multi-difference SALIENCY map Salient region
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