APSIPA Transactions on Signal and Information Processing > Vol 3 > Issue 1

Depth video coding based on intra mode inheritance from texture

Elie Gabriel Mora, Orange Labs, France, mora@telecom-paristech.fr , Joel Jung, Orange Labs, France, Marco Cagnazzo, Telecom ParisTech, France, Béatrice Pesquet-Popescu, Telecom ParisTech, France
 
Suggested Citation
Elie Gabriel Mora, Joel Jung, Marco Cagnazzo and Béatrice Pesquet-Popescu (2014), "Depth video coding based on intra mode inheritance from texture", APSIPA Transactions on Signal and Information Processing: Vol. 3: No. 1, e1. http://dx.doi.org/10.1017/ATSIP.2013.8

Publication Date: 07 Jan 2014
© 2014 Elie Gabriel Mora, Joel Jung, Marco Cagnazzo and Béatrice Pesquet-Popescu
 
Subjects
 
Keywords
Depth video codingIntra mode inheritanceEdge detectionInheritance CriterionMost probable mode
 

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This is published under the terms of the Creative Commons Attribution licence.

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In this article:
I. INTRODUCTION 
II. STATE OF THE ART 
III. PROPOSED INTRA MODE INHERITANCE TOOL AND GRADIENTMAX CRITERION 
IV. EXPERIMENTAL RESULTS WITH THE GRADIENTMAX CRITERION 
V. THE DOMINANTANGL CRITERION 
VI. EXPERIMENTAL RESULTS WITH THE DOMINANTANGLE CRITERION 
VII. CONCLUSION 

Abstract

With the recent development of new three-dimensional (3D) multimedia services such as 3D television or free viewpoint television, a new 3D video format, called multiview video + depth (MVD) is currently being investigated. MVD allows synthesizing as many views as required at the receiver side, thus providing smooth scene transitions and the ability to experience a new 3D perspective with each different viewing point. The format introduces, alongside traditional 2D image sequences, sequences of depth maps, which must be efficiently coded to achieve good quality for the synthesized views. One approach to code depth videos is to exploit the correlations between texture and depth. In this work, we propose a new tool to code depth videos in which the texture Intra modes are inherited and used as predictors for the depth Intra modes, hence reducing the mode signaling bitrate. The tool is only used in prediction units where texture and depth Intra directions, or modes, are expected to match. Two criteria that exploit the statistical dependency between the texture and depth Intra modes are studied in this work: GradientMax and DominantAngle. Average bitrate reductions of 1.3 and 1.6% on synthesized sequences are reported for GradientMax and DominantAngle, respectively. The latter method additionally achieves 2.3% bitrate reduction on depth sequences.

DOI:10.1017/ATSIP.2013.8