Paper
16 September 1996 MPEG-2 variable bit rate coding algorithm: analysis and modeling
Antonio Chimienti, Marco Conti, Enrico Gregori, Maurizio Lucenteforte, Romualdo Picco
Author Affiliations +
Abstract
Variable bit rate (VBR) video is currently by far the most interesting and challenging real-time application for B- ISDN/ATM environments. To define bandwidth allocation schemes which provide an adequate quality of service (QoS) for VBR applications and minimize the waste of bandwidth, the effects of the video applications on the network must be investigated. While the modeling of VBR video sources has recently received significant attention, there presently exists no widely accepted model which lends itself to mathematical analysis. Currently MPEG is the reference standard for moving video compression. In the first part of the paper a VBR implementation of MPEG-2 coding algorithm is described and a comparison with the constant bit rate (CBR) algorithm is performed. To investigate the impact that the coding parameters have on the characteristics of the traffic delivered to the network a long sample of the movie 'The Sheltering Sky' has been coded with two different quantizer steps. The generated trace was used to obtain a detailed statistical analysis of the traffic generated by an MPEG-2 encoder. Starting from this statistical analysis an analytically tractable model is developed, analyzed and used to study bandwidth allocation problems.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Antonio Chimienti, Marco Conti, Enrico Gregori, Maurizio Lucenteforte, and Romualdo Picco "MPEG-2 variable bit rate coding algorithm: analysis and modeling", Proc. SPIE 2952, Digital Compression Technologies and Systems for Video Communications, (16 September 1996); https://doi.org/10.1117/12.251326
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Cited by 5 scholarly publications.
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KEYWORDS
Statistical analysis

Video

Quantization

Computer programming

Mathematical modeling

Video compression

Statistical modeling

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