Study of Coding Units Depth for Depth Maps Quality Scalable Compression Using SHVC

Dorsaf Sebai, Faouzi Ghorbel, Sounia Messbahi

2023

Abstract

Scalable High Efficiency Video Coding (SHVC) is used to adaptively encode texture images. SHVC architecture is composed of Base and Enhancement Layers (BL and EL), with an interlayer picture processing module between them. In order to ensure effective encoding, each picture is divided into a certain number of Coding Units (CUs), with different depths, composing the Coding Tree Unit (CTU). Being initially dedicated to texture images, SHVC does not provide the same efficiency when applied to depth maps. To understand the causes behind, we propose to study the SHVC CTU partitioning for depth maps. This can be a starting point to propose an efficient 3D video scalable compression. Main observations of this study show that the depth of most CUs is 2 and 3 for texture images. However, this depth is either 0 or 1 for depth maps. Moreover, CUs depths frequently change when passing from the base and enhancement layers of SHVC for the non-flat regions. This is not the case for the smooth regions that generally preserve the same CUs depths in the two SHVC layers.

Paper Citation

in Harvard Style

Sebai D., Ghorbel F. and Messbahi S. (2023). Study of Coding Units Depth for Depth Maps Quality Scalable Compression Using SHVC. In Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 4: VISAPP; ISBN 978-989-758-634-7, SciTePress, pages 114-120. DOI: 10.5220/0011706400003417

in Bibtex Style

@conference{visapp23,
author={Dorsaf Sebai and Faouzi Ghorbel and Sounia Messbahi},
title={Study of Coding Units Depth for Depth Maps Quality Scalable Compression Using SHVC},
booktitle={Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 4: VISAPP},
year={2023},
pages={114-120},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011706400003417},
isbn={978-989-758-634-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 4: VISAPP
TI - Study of Coding Units Depth for Depth Maps Quality Scalable Compression Using SHVC
SN - 978-989-758-634-7
AU - Sebai D.
AU - Ghorbel F.
AU - Messbahi S.
PY - 2023
SP - 114
EP - 120
DO - 10.5220/0011706400003417
PB - SciTePress