JOURNAL ARTICLE

Optimized transmission of H.26L/JVT coded video over packet-lossy networks

Thomas StockhammerThomas WiegandStephan Wenger

Year: 2003 Journal:   Proceedings - International Conference on Image Processing Vol: 2 Pages: II-173   Publisher: Institute of Electrical and Electronics Engineers

Abstract

Transmission of hybrid coded video including motion compensation and spatial prediction over error-prone channels results in the well-known problem of spatio-temporal error propagation at the decoder. A widely accepted standard-compliant technique to enhance the quality of the decoded video significantly is the more frequent introduction of intra-coded macroblocks. However, intra-coded information generally requires more bit rate. Therefore, a careful selection of intra-updates in terms of rate and distortion is necessary. A flexible and robust rate-distortion optimization technique is presented to select coding mode and reference frame for each macroblock. The channel statistics are included in the optimization process. We derive a method to obtain an estimate of the decoder pixel distortion at the encoder. The presented techniques are verified within the new H.26L/JVT video coding standard based on common test conditions.

Keywords:
Computer science Macroblock Motion compensation Encoder Rate–distortion optimization Lossy compression Network packet Reference frame Coding tree unit Algorithm Block-matching algorithm Decoding methods Computer vision Video tracking Artificial intelligence Frame (networking) Video processing Computer network

Metrics

32
Cited By
2.89
FWCI (Field Weighted Citation Impact)
12
Refs
0.92
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
Advanced Data Compression Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image and Video Quality Assessment
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
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