Robust estimator for 3D meshes filtering

Zhi Hong Mao; Li Zhuang Ma; Ming Xi Zhao

doi:10.1360/jos180453

Robust estimator for 3D meshes filtering

Zhi Hong Mao^*
, Li Zhuang Ma
, Ming Xi Zhao

^*此作品的通讯作者

Shanghai Jiao Tong University

科研成果: 期刊稿件 › 文章 › 同行评审

摘要

In this paper, the link between least-squares (LS) estimator and Laplacian smoothing method from the point of view of LS method is firstly disclosed. Further more, an M-estimator for mesh filtering is presented. At last, the M-estimator is extended to the re-weighted M-estimator to remove noise while preserving the surface feature efficiently. The re-weighted M-estimator is bilateral filtering in natural.

源语言	英语
页（从-至）	453-460
页数	8
期刊	Ruan Jian Xue Bao/Journal of Software
卷	18
期	2
DOI	https://doi.org/10.1360/jos180453
出版状态	已出版 - 2月 2007
已对外发布	是

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title = "Robust estimator for 3D meshes filtering",

abstract = "In this paper, the link between least-squares (LS) estimator and Laplacian smoothing method from the point of view of LS method is firstly disclosed. Further more, an M-estimator for mesh filtering is presented. At last, the M-estimator is extended to the re-weighted M-estimator to remove noise while preserving the surface feature efficiently. The re-weighted M-estimator is bilateral filtering in natural.",

keywords = "Feature preserving, Least-squares estimation, M-estimator, Mesh filtering, Re-weighted M-estimator",

author = "Mao, \{Zhi Hong\} and Ma, \{Li Zhuang\} and Zhao, \{Ming Xi\}",

year = "2007",

month = feb,

doi = "10.1360/jos180453",

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journal = "Ruan Jian Xue Bao/Journal of Software",

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AU - Mao, Zhi Hong

AU - Ma, Li Zhuang

AU - Zhao, Ming Xi

PY - 2007/2

Y1 - 2007/2

N2 - In this paper, the link between least-squares (LS) estimator and Laplacian smoothing method from the point of view of LS method is firstly disclosed. Further more, an M-estimator for mesh filtering is presented. At last, the M-estimator is extended to the re-weighted M-estimator to remove noise while preserving the surface feature efficiently. The re-weighted M-estimator is bilateral filtering in natural.

AB - In this paper, the link between least-squares (LS) estimator and Laplacian smoothing method from the point of view of LS method is firstly disclosed. Further more, an M-estimator for mesh filtering is presented. At last, the M-estimator is extended to the re-weighted M-estimator to remove noise while preserving the surface feature efficiently. The re-weighted M-estimator is bilateral filtering in natural.

KW - Feature preserving

KW - Least-squares estimation

KW - M-estimator

KW - Mesh filtering

KW - Re-weighted M-estimator

UR - https://www.scopus.com/pages/publications/34147202514

U2 - 10.1360/jos180453

DO - 10.1360/jos180453

M3 - 文章

AN - SCOPUS:34147202514

SN - 1000-9825

VL - 18

SP - 453

EP - 460

JO - Ruan Jian Xue Bao/Journal of Software

JF - Ruan Jian Xue Bao/Journal of Software

IS - 2

ER -

Robust estimator for 3D meshes filtering

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