Denoising time-of-flight data with adaptive total variation

Authors:
Frank Lenzen;Henrik Schäfer;Christoph Garbe
Affiliations:
Heidelberg Collaboratory for Image Processing, Heidelberg University and Intel Visual Computing Institute, Saarland University;Heidelberg Collaboratory for Image Processing, Heidelberg University and Intel Visual Computing Institute, Saarland University;Heidelberg Collaboratory for Image Processing, Heidelberg University and Intel Visual Computing Institute, Saarland University
Venue:
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part I
Year:
2011

Citing 10
Cited 1

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
Denoising with higher order derivatives of bounded variation and an application to parameter estimation

Computing
Non-Linear Gaussian Filters Performing Edge Preserving Diffusion

Mustererkennung 1995, 17. DAGM-Symposium
Bilateral Filtering for Gray and Color Images

ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Fast median and bilateral filtering

ACM SIGGRAPH 2006 Papers
Anisotropic Smoothing Using Double Orientations

SSVM '09 Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision
A Clustering Based Denoising Technique for Range Images of Time of Flight Cameras

CIMCA '08 Proceedings of the 2008 International Conference on Computational Intelligence for Modelling Control & Automation
A Physical Model of Time-of-Flight 3D Imaging Systems, Including Suppression of Ambient Light

Dyn3D '09 Proceedings of the DAGM 2009 Workshop on Dynamic 3D Imaging
Total Generalized Variation

SIAM Journal on Imaging Sciences
Variational image denoising with adaptive constraint sets

SSVM'11 Proceedings of the Third international conference on Scale Space and Variational Methods in Computer Vision

High accuracy TOF and stereo sensor fusion at interactive rates

ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume 2

Quantified Score

Hi-index	0.00

Visualization

Abstract

For denoising depth maps from time-of-flight (ToF) cameras we propose an adaptive total variation based approach of first and second order. This approach allows us to take into account the geometric properties of the depth data, such as edges and slopes. To steer adaptivity we utilize a special kind of structure tensor based on both the amplitude and phase of the recorded ToF signal. A comparison to state-of-the-art denoising methods shows the advantages of our approach.