Guided Mesh Normal Filtering
The joint bilateral filter is a variant of the standard bilateral filter, where the range kernel is evaluated using a guidance signal instead of the original signal. It has been successfully applied to various image processing problems, where it provides more flexibility than the standard bilateral...
Saved in:
Published in | Computer graphics forum Vol. 34; no. 7; pp. 23 - 34 |
---|---|
Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Oxford
Blackwell Publishing Ltd
01.10.2015
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | The joint bilateral filter is a variant of the standard bilateral filter, where the range kernel is evaluated using a guidance signal instead of the original signal. It has been successfully applied to various image processing problems, where it provides more flexibility than the standard bilateral filter to achieve high quality results. On the other hand, its success is heavily dependent on the guidance signal, which should ideally provide a robust estimation about the features of the output signal. Such a guidance signal is not always easy to construct. In this paper, we propose a novel mesh normal filtering framework based on the joint bilateral filter, with applications in mesh denoising. Our framework is designed as a two‐stage process: first, we apply joint bilateral filtering to the face normals, using a properly constructed normal field as the guidance; afterwards, the vertex positions are updated according to the filtered face normals. We compute the guidance normal on a face using a neighboring patch with the most consistent normal orientations, which provides a reliable estimation of the true normal even with a high‐level of noise. The effectiveness of our approach is validated by extensive experimental results. |
---|---|
Bibliography: | Supporting InformationSupporting Information ArticleID:CGF12742 istex:B26749777A1B5E16A428080F36D4EB16B2104156 ark:/67375/WNG-2LVKD289-D SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0167-7055 1467-8659 |
DOI: | 10.1111/cgf.12742 |