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Journal ArticleDOI

A framework for efficient progressive fine granularity scalable video coding

Feng Wu, +2 more
- 01 Mar 2001 - 
- Vol. 11, Iss: 3, pp 332-344
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TLDR
Experimental results show that the PFGS framework can improve the coding efficiency up to more than 1 dB over the FGS scheme in terms of average PSNR, yet still keeps all the original properties, such as fine granularity, bandwidth adaptation, and error recovery.
Abstract
A basic framework for efficient scalable video coding, namely progressive fine granularity scalable (PFGS) video coding is proposed. Similar to the fine granularity scalable (PGS) video coding in MPEG-4, the PFGS framework has all the features of FGS, such as fine granularity bit-rate scalability, channel adaptation, and error recovery. On the other hand, different from the PGS coding, the PFGS framework uses multiple layers of references with increasing quality to make motion prediction more accurate for improved video-coding efficiency. However, using multiple layers of references with different quality also introduces several issues. First, extra frame buffers are needed for storing the multiple reconstructed reference layers. This would increase the memory cost and computational complexity of the PFGS scheme. Based on the basic framework, a simplified and efficient PFGS framework is further proposed. The simplified PPGS framework needs only one extra frame buffer with almost the same coding efficiency as in the original framework. Second, there might be undesirable increase and fluctuation of the coefficients to be coded when switching from a low-quality reference to a high-quality one, which could partially offset the advantage of using a high-quality reference. A further improved PFGS scheme can eliminate the fluctuation of enhancement-layer coefficients when switching references by always using only one high-quality prediction reference for all enhancement layers. Experimental results show that the PFGS framework can improve the coding efficiency up to more than 1 dB over the FGS scheme in terms of average PSNR, yet still keeps all the original properties, such as fine granularity, bandwidth adaptation, and error recovery. A simple simulation of transmitting the PFGS video over a wireless channel further confirms the error robustness of the PFGS scheme, although the advantages of PFGS have not been fully exploited.

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Citations
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Fast Bitstream Switching Algorithms for Real-Time Adaptive Video Multicasting

TL;DR: Two new fast real-time bitstream switching algorithms that aim to minimize the drifting error, while avoiding the problems of long delay, high complexity and bit-rate overhead for storage and transmission that often occur in prior solutions are proposed.
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TL;DR: In this paper, an efficient data partitioning and coding algorithm for an error-resilient transmission of DCT coefficients in error prone environment is proposed and it is shown that the proposed algorithm provides a better image quality than the conventional methods with a little overhead.
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An optimal packetization scheme for fine granularity scalable bitstream

TL;DR: A very general performance metric for streaming FGS bitstreams over packet erasure networks is defined and analyzed and three packetization strategies, namely baseline packetization, binary-tree packetization and optimal packetization are presented, justified and compared.
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Error drifting reduction in enhanced fine granularity scalability

TL;DR: This work incorporates fading and reset mechanisms in an enhanced fine granularity scalability algorithm to reduce the drifting error at low bit rate while still maintaining 1.5dB PSNR gain at high bit rate over the current MPEG-4 fine granular scalability.
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Journal ArticleDOI

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