A Finite Volume Framework for Geometric Surface Processing
Abstract We present a surface denoising method using the vertex-centered finite volume method coupled with the mesh covariance fractional anisotropy. The approach is computationally fast and able to effectively remove undesirable noise while preserving prominent geometric features of a 3D mesh surfa...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Kacem, Anis [verfasserIn] Hamza, A. Ben [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2013 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Journal of VLSI signal processing systems for signal, image and video technology - Springer Netherlands, 1989, 76(2013), 1 vom: 28. Juli, Seite 63-75 |
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| Übergeordnetes Werk: |
volume:76 ; year:2013 ; number:1 ; day:28 ; month:07 ; pages:63-75 |
| Links: |
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| DOI / URN: |
10.1007/s11265-013-0807-6 |
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| 520 | |a Abstract We present a surface denoising method using the vertex-centered finite volume method coupled with the mesh covariance fractional anisotropy. The approach is computationally fast and able to effectively remove undesirable noise while preserving prominent geometric features of a 3D mesh surface such as curved surface regions, sharp edges, and fine details. Extensive experimental results on various 3D models demonstrate the effectiveness of the proposed iterative algorithm, which yields satisfactory output results in just one single iteration. | ||
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10.1007/s11265-013-0807-6 doi (DE-627)SPR018327400 (SPR)s11265-013-0807-6-e DE-627 ger DE-627 rakwb eng Kacem, Anis verfasserin aut A Finite Volume Framework for Geometric Surface Processing 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract We present a surface denoising method using the vertex-centered finite volume method coupled with the mesh covariance fractional anisotropy. The approach is computationally fast and able to effectively remove undesirable noise while preserving prominent geometric features of a 3D mesh surface such as curved surface regions, sharp edges, and fine details. Extensive experimental results on various 3D models demonstrate the effectiveness of the proposed iterative algorithm, which yields satisfactory output results in just one single iteration. 3D mesh denoising (dpeaa)DE-He213 Finite volume (dpeaa)DE-He213 Fractional anisotropy (dpeaa)DE-He213 Hamza, A. Ben verfasserin aut Enthalten in Journal of VLSI signal processing systems for signal, image and video technology Springer Netherlands, 1989 76(2013), 1 vom: 28. Juli, Seite 63-75 (DE-627)SPR018308090 nnns volume:76 year:2013 number:1 day:28 month:07 pages:63-75 https://dx.doi.org/10.1007/s11265-013-0807-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_40 GBV_ILN_2006 GBV_ILN_2027 AR 76 2013 1 28 07 63-75 |
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10.1007/s11265-013-0807-6 doi (DE-627)SPR018327400 (SPR)s11265-013-0807-6-e DE-627 ger DE-627 rakwb eng Kacem, Anis verfasserin aut A Finite Volume Framework for Geometric Surface Processing 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract We present a surface denoising method using the vertex-centered finite volume method coupled with the mesh covariance fractional anisotropy. The approach is computationally fast and able to effectively remove undesirable noise while preserving prominent geometric features of a 3D mesh surface such as curved surface regions, sharp edges, and fine details. Extensive experimental results on various 3D models demonstrate the effectiveness of the proposed iterative algorithm, which yields satisfactory output results in just one single iteration. 3D mesh denoising (dpeaa)DE-He213 Finite volume (dpeaa)DE-He213 Fractional anisotropy (dpeaa)DE-He213 Hamza, A. Ben verfasserin aut Enthalten in Journal of VLSI signal processing systems for signal, image and video technology Springer Netherlands, 1989 76(2013), 1 vom: 28. Juli, Seite 63-75 (DE-627)SPR018308090 nnns volume:76 year:2013 number:1 day:28 month:07 pages:63-75 https://dx.doi.org/10.1007/s11265-013-0807-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_40 GBV_ILN_2006 GBV_ILN_2027 AR 76 2013 1 28 07 63-75 |
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10.1007/s11265-013-0807-6 doi (DE-627)SPR018327400 (SPR)s11265-013-0807-6-e DE-627 ger DE-627 rakwb eng Kacem, Anis verfasserin aut A Finite Volume Framework for Geometric Surface Processing 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract We present a surface denoising method using the vertex-centered finite volume method coupled with the mesh covariance fractional anisotropy. The approach is computationally fast and able to effectively remove undesirable noise while preserving prominent geometric features of a 3D mesh surface such as curved surface regions, sharp edges, and fine details. Extensive experimental results on various 3D models demonstrate the effectiveness of the proposed iterative algorithm, which yields satisfactory output results in just one single iteration. 3D mesh denoising (dpeaa)DE-He213 Finite volume (dpeaa)DE-He213 Fractional anisotropy (dpeaa)DE-He213 Hamza, A. Ben verfasserin aut Enthalten in Journal of VLSI signal processing systems for signal, image and video technology Springer Netherlands, 1989 76(2013), 1 vom: 28. Juli, Seite 63-75 (DE-627)SPR018308090 nnns volume:76 year:2013 number:1 day:28 month:07 pages:63-75 https://dx.doi.org/10.1007/s11265-013-0807-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_40 GBV_ILN_2006 GBV_ILN_2027 AR 76 2013 1 28 07 63-75 |
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Abstract We present a surface denoising method using the vertex-centered finite volume method coupled with the mesh covariance fractional anisotropy. The approach is computationally fast and able to effectively remove undesirable noise while preserving prominent geometric features of a 3D mesh surface such as curved surface regions, sharp edges, and fine details. Extensive experimental results on various 3D models demonstrate the effectiveness of the proposed iterative algorithm, which yields satisfactory output results in just one single iteration. |
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Abstract We present a surface denoising method using the vertex-centered finite volume method coupled with the mesh covariance fractional anisotropy. The approach is computationally fast and able to effectively remove undesirable noise while preserving prominent geometric features of a 3D mesh surface such as curved surface regions, sharp edges, and fine details. Extensive experimental results on various 3D models demonstrate the effectiveness of the proposed iterative algorithm, which yields satisfactory output results in just one single iteration. |
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Abstract We present a surface denoising method using the vertex-centered finite volume method coupled with the mesh covariance fractional anisotropy. The approach is computationally fast and able to effectively remove undesirable noise while preserving prominent geometric features of a 3D mesh surface such as curved surface regions, sharp edges, and fine details. Extensive experimental results on various 3D models demonstrate the effectiveness of the proposed iterative algorithm, which yields satisfactory output results in just one single iteration. |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR018327400</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20201124222412.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201006s2013 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s11265-013-0807-6</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR018327400</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s11265-013-0807-6-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Kacem, Anis</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="2"><subfield code="a">A Finite Volume Framework for Geometric Surface Processing</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2013</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract We present a surface denoising method using the vertex-centered finite volume method coupled with the mesh covariance fractional anisotropy. The approach is computationally fast and able to effectively remove undesirable noise while preserving prominent geometric features of a 3D mesh surface such as curved surface regions, sharp edges, and fine details. Extensive experimental results on various 3D models demonstrate the effectiveness of the proposed iterative algorithm, which yields satisfactory output results in just one single iteration.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">3D mesh denoising</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Finite volume</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Fractional anisotropy</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Hamza, A. Ben</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Journal of VLSI signal processing systems for signal, image and video technology</subfield><subfield code="d">Springer Netherlands, 1989</subfield><subfield code="g">76(2013), 1 vom: 28. Juli, Seite 63-75</subfield><subfield code="w">(DE-627)SPR018308090</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:76</subfield><subfield code="g">year:2013</subfield><subfield code="g">number:1</subfield><subfield code="g">day:28</subfield><subfield code="g">month:07</subfield><subfield code="g">pages:63-75</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://dx.doi.org/10.1007/s11265-013-0807-6</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_SPRINGER</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2006</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2027</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">76</subfield><subfield code="j">2013</subfield><subfield code="e">1</subfield><subfield code="b">28</subfield><subfield code="c">07</subfield><subfield code="h">63-75</subfield></datafield></record></collection>
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