Hierarchical SNR Scalable Video Coding with Adaptive Quantization for Reduced Drift Error

Roya Choupani, Stephan Wong, Mehmet Tolun

2015

Abstract

In video coding, dependencies between frames are being exploited to achieve compression by only coding the differences. This dependency can potentially lead to decoding inaccuracies when there is a communication error, or a deliberate quality reduction due to reduced network or receiver capabilities. The dependency can start at the reference frame and progress through a chain of dependent frames within a group of pictures (GOP) resulting in the so-called drift error. Scalable video coding schemes should deal with such drift errors while maximizing the delivered video quality. In this paper, we present a multi-layer hierarchical structure for scalable video coding capable of reducing the drift error. Moreover, we propose an optimization to adaptively determine the quantization step size for the base and enhancement layers. In addition, we address the trade-off between the drift error and the coding efficiency. The improvements in terms of average PSNR values when one frame in a GOP is lost are 3.70(dB) when only the base layer is delivered, and 4.78(dB) when both the base and the enhancement layers are delivered. The improvements in presence of burst errors are 3.52(dB) when only the base layer is delivered, and 4.50(dB) when both base and enhancement layers are delivered.

Paper Citation

in Harvard Style

Choupani R., Wong S. and Tolun M. (2015). Hierarchical SNR Scalable Video Coding with Adaptive Quantization for Reduced Drift Error . In Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015) ISBN 978-989-758-089-5, pages 117-123. DOI: 10.5220/0005306001170123

in Bibtex Style

@conference{visapp15,
author={Roya Choupani and Stephan Wong and Mehmet Tolun},
title={Hierarchical SNR Scalable Video Coding with Adaptive Quantization for Reduced Drift Error},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015)},
year={2015},
pages={117-123},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005306001170123},
isbn={978-989-758-089-5},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015)
TI - Hierarchical SNR Scalable Video Coding with Adaptive Quantization for Reduced Drift Error
SN - 978-989-758-089-5
AU - Choupani R.
AU - Wong S.
AU - Tolun M.
PY - 2015
SP - 117
EP - 123
DO - 10.5220/0005306001170123