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Article: A Robust High-Resolution Details Preserving Denoising Algorithm for Meshes

TitleA Robust High-Resolution Details Preserving Denoising Algorithm for Meshes
Authors
KeywordsFace neighborhood
High-resolution details
Mesh denoising
Normal clustering
Normal filtering
Issue Date2013
PublisherScience China Press, co-published with Springer Berlin Heidelberg. The Journal's web site is located at http://info.scichina.com/
Citation
Science China Information Sciences, 2013, v. 56 n. 9, p. 1-12 How to Cite?
AbstractFinely captured meshes often contain details like sharp edges, corners and shallow features. In order to improve the quality of these meshes, we present a robust and efficient high-resolution details-preserving mesh denoising algorithm. Our method consists of three stages. For each triangular face and its face neighborhood, we improve a robust density-based clustering method and apply it to the face neighborhood to extract a subset of neighbors which belong to the same cluster as the central face. And then, we filter the central face normal iteratively within this subset to remove noise. Because the faces within the extracted subset are not distributed across high-resolution details, our normal filtering can preserve such details as much as possible. Finally, we update the vertex positions to be consistent with the filtered face normals using a least-squares formulation. Experiments on various types of meshes indicate that our method has advantages over previous surface denoising methods.
Persistent Identifierhttp://hdl.handle.net/10722/204712
ISSN
2017 Impact Factor: 2.188
2015 SCImago Journal Rankings: 0.427
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorFan, H-
dc.contributor.authorPeng, Q-
dc.contributor.authorYu, Y-
dc.date.accessioned2014-09-20T00:31:37Z-
dc.date.available2014-09-20T00:31:37Z-
dc.date.issued2013-
dc.identifier.citationScience China Information Sciences, 2013, v. 56 n. 9, p. 1-12-
dc.identifier.issn1674-733X-
dc.identifier.urihttp://hdl.handle.net/10722/204712-
dc.description.abstractFinely captured meshes often contain details like sharp edges, corners and shallow features. In order to improve the quality of these meshes, we present a robust and efficient high-resolution details-preserving mesh denoising algorithm. Our method consists of three stages. For each triangular face and its face neighborhood, we improve a robust density-based clustering method and apply it to the face neighborhood to extract a subset of neighbors which belong to the same cluster as the central face. And then, we filter the central face normal iteratively within this subset to remove noise. Because the faces within the extracted subset are not distributed across high-resolution details, our normal filtering can preserve such details as much as possible. Finally, we update the vertex positions to be consistent with the filtered face normals using a least-squares formulation. Experiments on various types of meshes indicate that our method has advantages over previous surface denoising methods.-
dc.languageeng-
dc.publisherScience China Press, co-published with Springer Berlin Heidelberg. The Journal's web site is located at http://info.scichina.com/-
dc.relation.ispartofScience China Information Sciences-
dc.subjectFace neighborhood-
dc.subjectHigh-resolution details-
dc.subjectMesh denoising-
dc.subjectNormal clustering-
dc.subjectNormal filtering-
dc.titleA Robust High-Resolution Details Preserving Denoising Algorithm for Meshes-
dc.typeArticle-
dc.identifier.emailYu, Y: yzyu@cs.hku.hk-
dc.identifier.authorityYu, Y=rp01415-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/s11432-013-4993-4-
dc.identifier.scopuseid_2-s2.0-84883828425-
dc.identifier.hkuros236485-
dc.identifier.volume56-
dc.identifier.issue9-
dc.identifier.spage1-
dc.identifier.epage12-
dc.identifier.isiWOS:000324164600004-
dc.publisher.placeChina-

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