标题:Noisy image segmentation based on approximate geodesic distance
作者:Gao, Shanshan ;Chi, Jing ;Liu, Cuiyun ;Zhang, Caiming
作者机构:[Gao, Shanshan ;Chi, Jing ;Zhang, Caiming ] School of Computer Science and Technology, Shandong University of Finance and Economics, Ji'nan; 250014, C 更多
通讯作者:Gao, Shanshan
来源:Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics
出版年:2014
卷:26
期:12
页码:2214-2222
摘要:Segmentation for noisy images is a difficult topic in image processing. To break through the restriction of Euclidean distance and segment the noisy image effectively, a new method based on a geodesic framework and EWCVT (edge-weighted centroidal Voronoi tessellation) energy model is presented in this paper. Firstly, we propose an approximate model of geodesic distance according to image gradient, which can decrease the computation complexity of the algorithm greatly. Then, we apply this geodesic distance to achieve anti noisy image segmentation by minimizing EWCVT energy. Experimental results show that the proposed method can carry out anti noisy segmentation effectively.
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收录类别:EI
资源类型:期刊论文
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