Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
A signal processing approach to fair surface design
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
The approximation power of moving least-squares
Mathematics of Computation
Implicit fairing of irregular meshes using diffusion and curvature flow
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Fast texture synthesis using tree-structured vector quantization
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Spectral processing of point-sampled geometry
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Digital Picture Processing
Proceedings of the conference on Visualization '01
Geometric surface smoothing via anisotropic diffusion of normals
Proceedings of the conference on Visualization '02
Texture Synthesis by Non-Parametric Sampling
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Non-iterative, feature-preserving mesh smoothing
ACM SIGGRAPH 2003 Papers
ACM SIGGRAPH 2003 Papers
SMI '02 Proceedings of the Shape Modeling International 2002 (SMI'02)
Bilateral Filtering for Gray and Color Images
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
ACM SIGGRAPH 2004 Papers
Spacetime faces: high resolution capture for modeling and animation
ACM SIGGRAPH 2004 Papers
Context-based surface completion
ACM SIGGRAPH 2004 Papers
Spacetime Stereo: A Unifying Framework for Depth from Triangulation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Non-Local Algorithm for Image Denoising
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Robust moving least-squares fitting with sharp features
ACM SIGGRAPH 2005 Papers
Video enhancement using per-pixel virtual exposures
ACM SIGGRAPH 2005 Papers
Unsupervised, Information-Theoretic, Adaptive Image Filtering for Image Restoration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Anisotropic smoothing of point sets
Computer Aided Geometric Design - Special issue: Geometric modelling and differential geometry
Smoothing by Example: Mesh Denoising by Averaging with Similarity-Based Weights
SMI '06 Proceedings of the IEEE International Conference on Shape Modeling and Applications 2006
An adaptive MLS surface for reconstruction with guarantees
SGP '05 Proceedings of the third Eurographics symposium on Geometry processing
A fast approximation of the bilateral filter using a signal processing approach
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
Uncertainty and variability in point cloud surface data
SPBG'04 Proceedings of the First Eurographics conference on Point-Based Graphics
Robust filtering of noisy scattered point data
SPBG'05 Proceedings of the Second Eurographics / IEEE VGTC conference on Point-Based Graphics
Consolidation of low-quality point clouds from outdoor scenes
SGP '13 Proceedings of the Eleventh Eurographics/ACMSIGGRAPH Symposium on Geometry Processing
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We present a new method for noise removal on static and time-varying range data. Our approach predicts the restored position of a perturbed vertex using similar vertices in its neighborhood. It defines the required similarity measure in a new non-local fashion which compares regions of the surface instead of point pairs. This allows our algorithm to obtain a more accurate denoising result than previous state-of-the-art approaches and, at the same time, to better preserve fine features of the surface. Another interesting component of our method is that the neighborhood size is not constant over the surface but adapted close to the boundaries which improves the denoising performance in those regions of the dataset. Furthermore, our approach is easy to implement, effective, and flexibly applicable to different types of scanned data. We demonstrate this on several static and interesting new time-varying datasets obtained using laser and structured light scanners.