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Article: Variational fuzzy mumford-shah model for image segmentation
Title | Variational fuzzy mumford-shah model for image segmentation |
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Authors | |
Keywords | Segmentation Fuzzy membership functions Mumford-Shah model Operator splitting Total variation |
Issue Date | 2010 |
Citation | SIAM Journal on Applied Mathematics, 2010, v. 70, n. 7, p. 2750-2770 How to Cite? |
Abstract | In this paper, we propose a variational fuzzy Mumford-Shah model for image segmentation. The model is based on the assumption that an image can be approximated by the product of a smooth function and a piecewise constant function. Image segmentation is achieved by minimizing the energy functional in terms of membership functions, which take values between 0 and 1 to accommodate the uncertainty of the membership of the pixels, and the partial volume effect inmedical images. We show the existence and symmetry of minimizers for the proposed energy minimization problem. The energy can be minimized by an efficient iterative algorithm. Our iterative method has been applied to medical images and natural images with good results. Comparisons with other segmentation methods demonstrate the advantage of our method in the presence of intensity inhomogeneities. © 2010 Society for Industrial and Applied Mathematics. |
Persistent Identifier | http://hdl.handle.net/10722/276868 |
ISSN | 2023 Impact Factor: 1.9 2023 SCImago Journal Rankings: 0.939 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Li, Fang | - |
dc.contributor.author | Ng, Michael K. | - |
dc.contributor.author | Li, Chunming | - |
dc.date.accessioned | 2019-09-18T08:34:54Z | - |
dc.date.available | 2019-09-18T08:34:54Z | - |
dc.date.issued | 2010 | - |
dc.identifier.citation | SIAM Journal on Applied Mathematics, 2010, v. 70, n. 7, p. 2750-2770 | - |
dc.identifier.issn | 0036-1399 | - |
dc.identifier.uri | http://hdl.handle.net/10722/276868 | - |
dc.description.abstract | In this paper, we propose a variational fuzzy Mumford-Shah model for image segmentation. The model is based on the assumption that an image can be approximated by the product of a smooth function and a piecewise constant function. Image segmentation is achieved by minimizing the energy functional in terms of membership functions, which take values between 0 and 1 to accommodate the uncertainty of the membership of the pixels, and the partial volume effect inmedical images. We show the existence and symmetry of minimizers for the proposed energy minimization problem. The energy can be minimized by an efficient iterative algorithm. Our iterative method has been applied to medical images and natural images with good results. Comparisons with other segmentation methods demonstrate the advantage of our method in the presence of intensity inhomogeneities. © 2010 Society for Industrial and Applied Mathematics. | - |
dc.language | eng | - |
dc.relation.ispartof | SIAM Journal on Applied Mathematics | - |
dc.subject | Segmentation | - |
dc.subject | Fuzzy membership functions | - |
dc.subject | Mumford-Shah model | - |
dc.subject | Operator splitting | - |
dc.subject | Total variation | - |
dc.title | Variational fuzzy mumford-shah model for image segmentation | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1137/090753887 | - |
dc.identifier.scopus | eid_2-s2.0-77956246296 | - |
dc.identifier.volume | 70 | - |
dc.identifier.issue | 7 | - |
dc.identifier.spage | 2750 | - |
dc.identifier.epage | 2770 | - |
dc.identifier.isi | WOS:000281108800031 | - |
dc.identifier.issnl | 0036-1399 | - |