JOURNAL ARTICLE

Error-resilient video coding using motion compensated temporal filtering and embedded multiple description scalar quantizers

Abstract

Real time delivery of video over best-effort networks requires compression systems that dynamically adapt the rate to the available channel capacity and exhibit robustness to data loss as retransmission is often impractical. Error-resilience, however, significantly lowers the coding performance when rigid design is performed based on a worst-case scenario. This paper presents an original scalable video coding scheme that couples the compression efficiency of the open-loop architecture with the robustness of multiple description source coding. The use of embedded multiple description quantization and a novel channel-aware rate-allocation allow for shaping on-the-fly the output bit-rate and the degree of resilience. As a result, robustness to data losses is traded for better visual quality when transmission occurs over reliable channels, while error-resilience is introduced when noisy links are involved. The advantage of our proposal is demonstrated in the context of packet-lossy networks.

Keywords:
Computer science Robustness (evolution) Real-time computing Lossy compression Multiple description coding Data compression Coding tree unit Packet loss Computer engineering Network packet Decoding methods Computer network Algorithm Artificial intelligence

Metrics

2
Cited By
0.57
FWCI (Field Weighted Citation Impact)
9
Refs
0.69
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Topics

Advanced Data Compression Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Video Coding and Compression Technologies
Physical Sciences →  Computer Science →  Signal Processing
Advanced Vision and Imaging
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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