2011
DOI: 10.1186/1687-6180-2011-131
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Denoising algorithm for the 3D depth map sequences based on multihypothesis motion estimation

Abstract: This article proposes an efficient wavelet-based depth video denoising approach based on a multihypothesis motion estimation aimed specifically at time-of-flight depth cameras. We first propose a novel bidirectional block matching search strategy, which uses information from the luminance as well as from the depth video sequence. Next, we present a new denoising technique based on weighted averaging and wavelet thresholding. Here we take into account the reliability of the estimated motion and the spatial vari… Show more

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Cited by 2 publications
(1 citation statement)
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“…The edge prediction sub-network generates an edge guidance map that is used to guide the depth reconstruction sub-network in recovering sharp edges and fine constructions. [73] proposes a time-of-flight depth camera-specific wavelet-based depth video denoising approach based on multi hypothesis motion estimation for facial depth maps. In [74] authors proposed a method and system for super-solving and recovering the facial depth maps.…”
Section: E Facial Depth Map Denoisingmentioning
confidence: 99%
“…The edge prediction sub-network generates an edge guidance map that is used to guide the depth reconstruction sub-network in recovering sharp edges and fine constructions. [73] proposes a time-of-flight depth camera-specific wavelet-based depth video denoising approach based on multi hypothesis motion estimation for facial depth maps. In [74] authors proposed a method and system for super-solving and recovering the facial depth maps.…”
Section: E Facial Depth Map Denoisingmentioning
confidence: 99%