ML Anthology

Robust Non-Local Denoising of Colored Depth Data

Benjamin Huhle, Timo Schairer, Philipp Jenke, Wolfgang Straßer
CVPRW 2008 pp. 1-7
doi:10.1109/CVPRW.2008.4563158 /cvprw/2008/huhle2008cvprw-robust/

Abstract

We give a brief discussion of denoising algorithms for depth data and introduce a novel technique based on the NL-Means Filter. A unified approach is presented that removes outliers from depth data and accordingly achieves an unbiased smoothing result. This robust denoising algorithm takes intra-patch similarity and optional color information into account in order to handle strong discontinuities and to preserve fine detail structure in the data. We achieve fast computation times with a GPU-based implementation. Results using data from a time-of-flight camera system show a significant gain in visual quality.

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Cite

Text

Huhle et al. "Robust Non-Local Denoising of Colored Depth Data." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2008. doi:10.1109/CVPRW.2008.4563158

Markdown

[Huhle et al. "Robust Non-Local Denoising of Colored Depth Data." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2008.](https://mlanthology.org/cvprw/2008/huhle2008cvprw-robust/) doi:10.1109/CVPRW.2008.4563158

BibTeX

@inproceedings{huhle2008cvprw-robust,
  title     = {{Robust Non-Local Denoising of Colored Depth Data}},
  author    = {Huhle, Benjamin and Schairer, Timo and Jenke, Philipp and Straßer, Wolfgang},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2008},
  pages     = {1-7},
  doi       = {10.1109/CVPRW.2008.4563158},
  url       = {https://mlanthology.org/cvprw/2008/huhle2008cvprw-robust/}
}