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Sensors 2015, 15(8), 18506-18525;

Temporal and Spatial Denoising of Depth Maps

Department of Computer Science and Information Engineering, National Taipei University, New Taipei City 23741, Taiwan
Department of Biomedical Engineering, Yuanpei University of Medical Technology, Hsinchu 30015, Taiwan
Department of Software Engineering and Management, National Kaohsiung Normal University, Kaohsiung 82444, Taiwan
Graduate Institute of Electronics Engineering, National Taiwan University, Taipei 10617, Taiwan
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M.N. Passaro
Received: 3 May 2015 / Revised: 22 July 2015 / Accepted: 23 July 2015 / Published: 29 July 2015
(This article belongs to the Section Physical Sensors)
Full-Text   |   PDF [2168 KB, uploaded 29 July 2015]   |  


This work presents a procedure for refining depth maps acquired using RGB-D (depth) cameras. With numerous new structured-light RGB-D cameras, acquiring high-resolution depth maps has become easy. However, there are problems such as undesired occlusion, inaccurate depth values, and temporal variation of pixel values when using these cameras. In this paper, a proposed method based on an exemplar-based inpainting method is proposed to remove artefacts in depth maps obtained using RGB-D cameras. Exemplar-based inpainting has been used to repair an object-removed image. The concept underlying this inpainting method is similar to that underlying the procedure for padding the occlusions in the depth data obtained using RGB-D cameras. Therefore, our proposed method enhances and modifies the inpainting method for application in and the refinement of RGB-D depth data image quality. For evaluating the experimental results of the proposed method, our proposed method was tested on the Tsukuba Stereo Dataset, which contains a 3D video with the ground truths of depth maps, occlusion maps, RGB images, the peak signal-to-noise ratio, and the computational time as the evaluation metrics. Moreover, a set of self-recorded RGB-D depth maps and their refined versions are presented to show the effectiveness of the proposed method. View Full-Text
Keywords: depth image; spatial-temporal denoising; RGB-D sensor; hole padding depth image; spatial-temporal denoising; RGB-D sensor; hole padding

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Lin, B.-S.; Su, M.-J.; Cheng, P.-H.; Tseng, P.-J.; Chen, S.-J. Temporal and Spatial Denoising of Depth Maps. Sensors 2015, 15, 18506-18525.

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