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Depth Image Post-processing Method by Diffusion
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems. (Realistic3D)
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems. (Realistic3D)
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems. (Realistic3D)
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems. (Realistic3D)
2013 (English)In: Proceedings of SPIE-The International Society for Optical Engineering: 3D Image Processing (3DIP) and Applications, SPIE - International Society for Optical Engineering, 2013, Art. no. 865003- p.Conference paper, (Refereed)
Abstract [en]

Multi-view three-dimensional television relies on view synthesis to reduce the number of views being transmitted.  Arbitrary views can be synthesized by utilizing corresponding depth images with textures. The depth images obtained from stereo pairs or range cameras may contain erroneous values, which entail artifacts in a rendered view. Post-processing of the data may then be utilized to enhance the depth image with the purpose to reach a better quality of synthesized views. We propose a Partial Differential Equation (PDE)-based interpolation method for a reconstruction of the smooth areas in depth images, while preserving significant edges. We modeled the depth image by adjusting thresholds for edge detection and a uniform sparse sampling factor followed by the second order PDE interpolation. The objective results show that a depth image processed by the proposed method can achieve a better quality of synthesized views than the original depth image. Visual inspection confirmed the results.

Place, publisher, year, edition, pages
SPIE - International Society for Optical Engineering, 2013. Art. no. 865003- p.
Keyword [en]
Depth image, post-processing, view synthesis
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:miun:diva-18537DOI: 10.1117/12.2003183ISI: 000322110500001Scopus ID: 2-s2.0-84878288330Local ID: STCISBN: 978-081949423-8 (print)OAI: oai:DiVA.org:miun-18537DiVA: diva2:608477
Conference
3D Image Processing (3DIP) and Applications 2013; 3-7 Feb 2013; Burlingame, Ca, USA; Conference 8650
Available from: 2013-02-27 Created: 2013-02-27 Last updated: 2016-10-20
In thesis
1. Coding of three-dimensional video content: Depth image coding by diffusion
Open this publication in new window or tab >>Coding of three-dimensional video content: Depth image coding by diffusion
2013 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Three-dimensional (3D) movies in theaters have become a massive commercial success during recent years, and it is likely that, with the advancement of display technologies and the production of 3D contents, TV broadcasting in 3D will play an important role in home entertainments in the not too distant future. 3D video contents contain at least two views from different perspectives for the left and the right eye of viewers. The amount of coded information is doubled if these views are encoded separately. Moreover, for multi-view displays (i.e. different perspectives of a scene in 3D are presented to the viewer at the same time through different angles), either video streams of all the required views must be transmitted to the receiver, or the displays must synthesize the missing views with a subset of the views. The latter approach has been widely proposed to reduce the amount of data being transmitted. The virtual views can be synthesized by the Depth Image Based Rendering (DIBR) approach from textures and associated depth images. However it is still the case that the amount of information for the textures plus the depths presents a significant challenge for the network transmission capacity. An efficient compression will, therefore, increase the availability of content access and provide a better video quality under the same network capacity constraints.

In this thesis, the compression of depth images is addressed. These depth images can be assumed as being piece-wise smooth. Starting from the properties of depth images, a novel depth image model based on edges and sparse samples is presented, which may also be utilized for depth image post-processing. Based on this model, a depth image coding scheme that explicitly encodes the locations of depth edges is proposed, and the coding scheme has a scalable structure. Furthermore, a compression scheme for block-based 3D-HEVC is also devised, in which diffusion is used for intra prediction. In addition to the proposed schemes, the thesis illustrates several evaluation methodologies, especially, the subjective test of the stimulus-comparison method. It is suitable for evaluating the quality of two impaired images, as the objective metrics are inaccurate with respect to synthesized views.

The MPEG test sequences were used for the evaluation. The results showed that virtual views synthesized from post-processed depth images by using the proposed model are better than those synthesized from original depth images. More importantly, the proposed coding schemes using such a model produced better synthesized views than the state of the art schemes. As a result, the outcome of the thesis can lead to a better quality of 3DTV experience.

Place, publisher, year, edition, pages
Sundsvall: Mid Sweden University, 2013. 36 p.
Series
Mid Sweden University licentiate thesis, ISSN 1652-8948
National Category
Engineering and Technology Signal Processing
Identifiers
urn:nbn:se:miun:diva-19087 (URN)STC (Local ID)978-91-87103-76-6 (ISBN)STC (Archive number)STC (OAI)
Presentation
(English)
Opponent
Supervisors
Available from: 2013-06-11 Created: 2013-06-06 Last updated: 2016-10-20Bibliographically approved

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Citation style
  • apa
  • harvard1
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  • Other style
More styles
Language
  • de-DE
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  • Other locale
More languages
Output format
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