Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Processing textured surfaces via anisotropic geometric diffusion.

Ulrich Clarenz1, Udo Diewald, Martin Rumpf

  • 1Institute for Numerical Analysis and Scientific Computing, University of Duisburg, 47048 Duisburg, Germany. clarenz@math.uni-duisburg.de

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|September 21, 2004
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Determining individual glomerular proteinuria and periglomerular infiltration in a cleared murine kidney by a 3-dimensional fast marching algorithm.

Kidney international·2024
Same author

Image Morphing in Deep Feature Spaces: Theory and Applications.

Journal of mathematical imaging and vision·2021
Same author

Statistical shape analysis of tap roots: a methodological case study on laser scanned sugar beets.

BMC bioinformatics·2020
Same author

Shape-Aware Matching of Implicit Surfaces Based on Thin Shell Energies.

Foundations of computational mathematics (New York, N.Y.)·2019
Same author

Joint reconstruction and classification of tumor cells and cell interactions in melanoma tissue sections with synthesized training data.

International journal of computer assisted radiology and surgery·2019
Same author

Functional Thin Films on Surfaces.

IEEE transactions on visualization and computer graphics·2017

This study introduces a novel multiscale surface processing method for smoothing noisy 3D scans. The technique enhances both surface geometry and texture details simultaneously, improving feature preservation.

Area of Science:

  • Computer Vision
  • Geometric Modeling
  • Image Processing

Background:

  • Modern scanning technologies generate noisy, textured, parametric surfaces.
  • Existing methods often struggle to simultaneously smooth surfaces and their associated textures.
  • Enhancing geometric and texture features while denoising is a significant challenge.

Purpose of the Study:

  • To present a multiscale method for fairing noisy, textured, parametric surfaces.
  • To adapt image processing techniques, specifically nonlinear diffusion equations, for surface processing.
  • To simultaneously smooth surfaces and textures while enhancing their features.

Main Methods:

  • A novel fairing method that simultaneously processes surface and texture.
  • Utilizes anisotropic curvature evolution for surface smoothing and anisotropic diffusion for texture processing.

Related Experiment Videos

  • Employs a finite element discretization for spatial aspects and finite difference for temporal aspects.
  • Incorporates a normal projection to prevent tangential drifting during surface evolution.

    • Main Results:

    • The method effectively smooths noisy triangulated surfaces and their textures.
    • Simultaneous processing leverages correlations between surface and texture edge features.
    • Diffusion tensors are dependent on regularized shape operators and texture gradients.
    • Demonstrated efficiency and flexibility across various applications.

    Conclusions:

    • The presented multiscale method offers a robust solution for processing noisy, textured surfaces.
    • The approach successfully enhances geometric and texture features while denoising.
    • The technique is adaptable and efficient for diverse surface processing tasks.