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- Publisher Website: 10.1016/j.cagd.2015.03.011
- Scopus: eid_2-s2.0-84941421545
- WOS: WOS:000356194100002
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Article: Denoising point sets via L0 minimization
Title | Denoising point sets via L0 minimization |
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Authors | |
Keywords | Point set Denoising L0 minimization L0 sparsity |
Issue Date | 2015 |
Publisher | Elsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/cagd |
Citation | Computer Aided Geometric Design, 2015, v. 35-36, p. 2-15 How to Cite? |
Abstract | We present an anisotropic point cloud denoising method using L0 minimization. The L0 norm directly measures the sparsity of a solution, and we observe that many common objects can be defined as piecewise smooth surfaces with a small number of features. Hence, we demonstrate how to apply an L0 optimization directly to point clouds, which produces sparser solutions and sharper surfaces than either the L1 or L2 norm. Our method can faithfully recover sharp features while at the same time smoothing the remaining regions even in the presence of large amounts of noise. |
Persistent Identifier | http://hdl.handle.net/10722/220471 |
ISSN | 2023 Impact Factor: 1.3 2023 SCImago Journal Rankings: 0.602 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Sun, Y | - |
dc.contributor.author | Schaefer, S | - |
dc.contributor.author | Wang, W | - |
dc.date.accessioned | 2015-10-16T06:43:19Z | - |
dc.date.available | 2015-10-16T06:43:19Z | - |
dc.date.issued | 2015 | - |
dc.identifier.citation | Computer Aided Geometric Design, 2015, v. 35-36, p. 2-15 | - |
dc.identifier.issn | 0167-8396 | - |
dc.identifier.uri | http://hdl.handle.net/10722/220471 | - |
dc.description.abstract | We present an anisotropic point cloud denoising method using L0 minimization. The L0 norm directly measures the sparsity of a solution, and we observe that many common objects can be defined as piecewise smooth surfaces with a small number of features. Hence, we demonstrate how to apply an L0 optimization directly to point clouds, which produces sparser solutions and sharper surfaces than either the L1 or L2 norm. Our method can faithfully recover sharp features while at the same time smoothing the remaining regions even in the presence of large amounts of noise. | - |
dc.language | eng | - |
dc.publisher | Elsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/cagd | - |
dc.relation.ispartof | Computer Aided Geometric Design | - |
dc.subject | Point set | - |
dc.subject | Denoising | - |
dc.subject | L0 minimization | - |
dc.subject | L0 sparsity | - |
dc.title | Denoising point sets via L0 minimization | - |
dc.type | Article | - |
dc.identifier.email | Sun, Y: yujing@hku.hk | - |
dc.identifier.email | Wang, W: wenping@cs.hku.hk | - |
dc.identifier.authority | Sun, Y=rp02880 | - |
dc.identifier.authority | Wang, W=rp00186 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1016/j.cagd.2015.03.011 | - |
dc.identifier.scopus | eid_2-s2.0-84941421545 | - |
dc.identifier.hkuros | 256020 | - |
dc.identifier.volume | 35-36 | - |
dc.identifier.spage | 2 | - |
dc.identifier.epage | 15 | - |
dc.identifier.isi | WOS:000356194100002 | - |
dc.publisher.place | Netherlands | - |