Prediction architecture based on block matching statistics for mixed spatial-resolution multi-view video coding

Article


Said, Hany, Moniri, M. and Chibelushi, Claude C. 2017. Prediction architecture based on block matching statistics for mixed spatial-resolution multi-view video coding. EURASIP Journal on Image and Video Processing. 2017 (1).
AuthorsSaid, Hany, Moniri, M. and Chibelushi, Claude C.
Abstract

The use of mixed spatial resolutions in multi-view video coding is a promising approach for coding videos efficiently at low bitrates. It can achieve a perceived quality, which is close to the view with the highest quality, according to the suppression theory of binocular vision. The aim of the work reported in this paper is to develop a new multi-view video coding technique suitable for low bitrate applications in terms of coding efficiency, computational and memory complexity, when coding videos, which contain either a single or multiple scenes. The paper proposes a new prediction architecture that addresses deficiencies of prediction architectures for multi-view video coding based on H.264/AVC. The prediction architectures which are used in mixed spatial-resolution multi-view video coding (MSR-MVC) are afflicted with significant computational complexity and require significant memory size, with regards to coding time and to the minimum number of reference frames. The architecture proposed herein is based on a set of investigations, which explore the effect of different inter-view prediction directions on the coding efficiency of multi-view video coding, conduct a comparative study of different decimation and interpolation methods, in addition to analyzing block matching statistics. The proposed prediction architecture has been integrated with an adaptive reference frame ordering algorithm, to provide an efficient coding solution for multi-view videos with hard scene changes. The paper includes a comparative performance assessment of the proposed architecture against an extended architecture based on the 3D digital multimedia broadcast (3D-DMB) and the Hierarchical B-Picture (HBP) architecture, which are two most widely used architectures for MSR-MVC. The assessment experiments show that the proposed architecture needs less bitrate by on average 13.1 Kbps, less coding time by 14% and less memory consumption by 31.6%, compared to a corresponding codec, which deploys the extended 3D-DMB architecture when coding single-scene videos. Furthermore, the codec, which deploys the proposed architecture, accelerates coding by on average 57% and requires 52% less memory, compared to a corresponding codec, which uses the HBP architecture. On the other hand, multi-view video coding which uses the proposed architecture needs more bitrate by on average 24.9 Kbps compared to a corresponding codec that uses the HBP architecture. For coding a multi-view video which has hard scene changes, the proposed architecture yields less bitrate (by on average 28.7 to 35.4 Kbps), and accelerates coding time (by on average 64 and 33%), compared to the HBP and extended 3D-DMB architectures, respectively. The proposed architecture will thus be most beneficial in low bitrate applications, which require multi-view video coding for video content depicting hard scene changes.

KeywordsH.264/AVC; Mixed spatial-resolution; Multi-view video coding; Prediction architecture
JournalEURASIP Journal on Image and Video Processing
Journal citation2017 (1)
ISSN1687-5281
1687-5176
Year2017
PublisherSpringerOpen
Publisher's version
License
CC BY
Digital Object Identifier (DOI)doi:10.1186/s13640-017-0164-7
Publication dates
Print13 Feb 2017
Publication process dates
Deposited16 May 2017
Accepted23 Jan 2017
FunderStaffordshire University
Staffordshire University
Copyright information© The authors 2017. Open Access - This article is distributed under the terms of the Creative Commons Attribution 4.0 International License CC-BY which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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