5107

Robust non-local denoising of colored depth data

Benjamin Huhle, Timo Schairer, Philipp Jenke, Wolfgang Strasser
University of Tubingen, WSI/GRIS, Sand 14, 72076 Tubingen, Germany
IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008. CVPRW ’08

@article{huhle2008robust,

   title={Robust non-local denoising of colored depth data},

   author={Huhle, B. and Schairer, T. and Jenke, P. and Stra{ss}er, W.},

   year={2008},

   publisher={IEEE}

}

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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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