Visual Saliency Detection Based on Region Contrast and Guided Filter
文献类型:会议论文
作者 | Liu, Liqiang1,2; Cao, Jianzhong1; Niu, Yuefeng1; Guo, Huinan1; Liu, LQ (reprint author), Chinese Acad Sci, Xian Inst Opt & Precis Mech, Xian, Shaanxi, Peoples R China. |
出版日期 | 2017 |
会议日期 | 2017-09-08 |
会议地点 | N China Univ Technol, Beijing, PEOPLES R CHINA |
关键词 | Saliency Guided Filter Region Contrast Edge And Texture |
页码 | 327-330 |
英文摘要 | The main challenge of previous saliency detection method is the low quality of obtained saliency map which missed the edge and texture information easily. So it cannot reflect the integrated image salient information. Considering this problem, we propose a novel saliency measure method which combine region contrast and fast guided filter. This method utilizes region contrast method to obtain initial saliency maps. Then we optimize the saliency maps by using the fast guided filter. Extensive experimental results on natural image show the effectiveness of the proposed method. One aspect, the obtained final saliency maps have obvious advantages in dealing with the texture and weakening the inconsequential region. Another aspect, evaluation on the two databases validates that our method achieves superior results and outperforms compared previous approach in both precision and recall. |
产权排序 | 1 |
会议录 | 2017 2ND IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND APPLICATIONS (ICCIA)
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会议录出版者 | IEEE |
学科主题 | Computer Science, Artificial Intelligence |
会议录出版地 | NEW YORK |
语种 | 英语 |
ISBN号 | 978-1-5386-2030-4 |
源URL | [http://ir.opt.ac.cn/handle/181661/29962] ![]() |
专题 | 西安光学精密机械研究所_动态光学成像研究室 |
通讯作者 | Liu, LQ (reprint author), Chinese Acad Sci, Xian Inst Opt & Precis Mech, Xian, Shaanxi, Peoples R China. |
作者单位 | 1.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Xian, Shaanxi, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China |
推荐引用方式 GB/T 7714 | Liu, Liqiang,Cao, Jianzhong,Niu, Yuefeng,et al. Visual Saliency Detection Based on Region Contrast and Guided Filter[C]. 见:. N China Univ Technol, Beijing, PEOPLES R CHINA. 2017-09-08. |
入库方式: OAI收割
来源:西安光学精密机械研究所
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