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New normalized nonlocal hybrid level set method for image segmentation 被引量:1

New normalized nonlocal hybrid level set method for image segmentation
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摘要 This article introduces a new normalized nonlocal hybrid level set method for image segmentation.Due to intensity overlapping,blurred edges with complex backgrounds,simple intensity and texture information,such kind of image segmentation is still a challenging task.The proposed method uses both the region and boundary information to achieve accurate segmentation results.The region information can help to identify rough region of interest and prevent the boundary leakage problem.It makes use of normalized nonlocal comparisons between pairs of patches in each region,and a heuristic intensity model is proposed to suppress irrelevant strong edges and constrain the segmentation.The boundary information can help to detect the precise location of the target object,it makes use of the geodesic active contour model to obtain the target boundary.The corresponding variational segmentation problem is implemented by a level set formulation.We use an internal energy term for geometric active contours to penalize the deviation of the level set function from a signed distance function.At last,experimental results on synthetic images and real images are shown in the paper with promising results. This article introduces a new normalized nonlocal hybrid level set method for image segmentation.Due to intensity overlapping,blurred edges with complex backgrounds,simple intensity and texture information,such kind of image segmentation is still a challenging task.The proposed method uses both the region and boundary information to achieve accurate segmentation results.The region information can help to identify rough region of interest and prevent the boundary leakage problem.It makes use of normalized nonlocal comparisons between pairs of patches in each region,and a heuristic intensity model is proposed to suppress irrelevant strong edges and constrain the segmentation.The boundary information can help to detect the precise location of the target object,it makes use of the geodesic active contour model to obtain the target boundary.The corresponding variational segmentation problem is implemented by a level set formulation.We use an internal energy term for geometric active contours to penalize the deviation of the level set function from a signed distance function.At last,experimental results on synthetic images and real images are shown in the paper with promising results.
出处 《Applied Mathematics(A Journal of Chinese Universities)》 SCIE CSCD 2017年第4期407-421,共15页 高校应用数学学报(英文版)(B辑)
基金 supported in part by the National Natural Science Foundation of China(11626214,11571309) the General Research Project of Zhejiang Provincial Department of Education(Y201635378) the Zhejiang Provincial Natural Science Foundation of China(LY17F020011) J.Peng is supported by the National Natural Science Foundation of China(11771160) the Research Promotion Program of Huaqiao University(ZQN-PY411) Natural Science Foundation of Fujian Province(2015J01254)
关键词 image segmentation level set method nonlocal method intensity information active contours NORMALIZATION image segmentation level set method nonlocal method intensity information active contours normalization
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