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2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Robust non-local denoising of colored depth data
Anchorage, AK, USA
June 23-June 28
ISBN: 978-1-4244-2339-2
Benjamin Huhle, University of Tübingen, WSI/GRIS, Sand 14, 72076, Germany
Timo Schairer, University of Tübingen, WSI/GRIS, Sand 14, 72076, Germany
Philipp Jenke, University of Tübingen, WSI/GRIS, Sand 14, 72076, Germany
Wolfgang Strasser, University of Tübingen, WSI/GRIS, Sand 14, 72076, Germany
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.
Citation:
Benjamin Huhle, Timo Schairer, Philipp Jenke, Wolfgang Strasser, "Robust non-local denoising of colored depth data," cvprw, pp.1-7, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008
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