JOURNAL ARTICLE

Practical error concealment strategy for video streaming adopting scalable video coding

Chun‐Su ParkHyeong-Min NamSeung‐Won JungSeung-Jin BaekSung-Jea Ko

Year: 2009 Journal:   IEEE Transactions on Consumer Electronics Vol: 55 (3)Pages: 1606-1613   Publisher: Institute of Electrical and Electronics Engineers

Abstract

The scalable video coding (SVC) standard adopts four post-processing error concealment (EC) methods as a non-normative tool in order to conceal a lost picture in transmission. In this paper, we first introduce an error tracking model with which the concealment error and propagation error can be estimated. Then, we analyze the four EC methods using the error tracking model. Until now, there have been few studies on how to conceal SVC bitstream corrupted by burst errors. Based on the results of the error analysis, we propose a selection-based EC strategy to conceal burst errors for SVC bitstream. In the proposed strategy, one of the four EC methods is adaptively selected such that the visual degradation is minimized for each lost picture. The experimental results show that the proposed EC strategy can improve the EC performance without increasing the computational complexity. Moreover, the proposed strategy does not require any modification of the conventional SVC codec since it utilizes only the EC methods adopted in the standard.

Keywords:
Bitstream Computer science Codec Scalable Video Coding Scalability Coding (social sciences) Propagation of uncertainty Error detection and correction Real-time computing Encoding (memory) Decoding methods Algorithm Motion compensation Artificial intelligence Computer hardware

Metrics

9
Cited By
2.09
FWCI (Field Weighted Citation Impact)
15
Refs
0.89
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Video Coding and Compression Technologies
Physical Sciences →  Computer Science →  Signal Processing
Image and Video Quality Assessment
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Vision and Imaging
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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