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On the accuracy and complexity of rate-distortion models for fine-grained scalable video sequences

Authors:

Cheng-Hsin Hsu,

Mohamed HefeedaAuthors Info & Claims

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), Volume 4, Issue 2

Article No.: 15, Pages 1 - 22

https://doi.org/10.1145/1352012.1352019

Published: 16 May 2008 Publication History

Abstract

Rate-distortion (R-D) models are functions that describe the relationship between the bitrate and expected level of distortion in the reconstructed video stream. R-D models enable optimization of the received video quality in different network conditions. Several R-D models have been proposed for the increasingly popular fine-grained scalable video sequences. However, the models' relative performance has not been thoroughly analyzed. Moreover, the time complexity of each model is not known, nor is the range of bitrates in which the model produces valid results. This lack of quantitative performance analysis makes it difficult to select the model that best suits a target streaming system. In this article, we classify, analyze, and rigorously evaluate all R-D models proposed for FGS coders in the literature. We classify R-D models into three categories: analytic, empirical, and semi-analytic. We describe the characteristics of each category. We analyze the R-D models by following their mathematical derivations, scrutinizing the assumptions made, and explaining when the assumptions fail and why. In addition, we implement all R-D models, a total of eight, and evaluate them using a diverse set of video sequences. In our evaluation, we consider various source characteristics, diverse channel conditions, different encoding/decoding parameters, different frame types, and several performance metrics including accuracy, range of applicability, and time complexity of each model. We also present clear systematic ways (pseudo codes) for constructing various R-D models from a given video sequence. Based on our experimental results, we present a justified list of recommendations on selecting the best R-D models for video-on-demand, video conferencing, real-time, and peer-to-peer streaming systems.

References

[1]

Adjeroh, D. and Lee, M. 2004. Scene-adaptive transform domain video partitioning. IEEE Trans. Multimedia 6, 1, 58--69.

Digital Library

[2]

Center for Image Processing Research. 2006. http://www.cipr.rpi.edu/resource.

[3]

Chiang, T. and Zhang, Y. 1997. A new rate control scheme using quadratic rate distortion model. IEEE Trans. Circ. Syst. Video Techn. 7, 1, 246--250.

Digital Library

[4]

Dai, M. 2004. Rate-distortion analysis and traffic modeling of scalable video coders. Ph.D. thesis, Department of Electrical Engineering, Texas A&M University.

Digital Library

[5]

Dai, M. and Loguinov, D. 2003. Analysis of rate-distortion functions and congestion control in scalable Internet video streaming. In Proceedings of ACM International Workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV'03). Monterey, CA.

Digital Library

[6]

Dai, M., Loguinov, D., and Radha, H. 2003. Statistical analysis and distortion modeling of MPEG-4 FGS. In Proceedings of IEEE International Conference on Image Processing (ICIP'03). Barcelona, Spain.

[7]

Dai, M., Loguinov, D., and Radha, H. 2004. Rate-distortion modeling of scalable video coders. In Proceedings of IEEE International Conference on Image Processing (ICIP'04). Singapore.

[8]

Dai, M., Loguinov, D., and Radha, H. 2006. Rate-distortion analysis and quality control in scalable Internet streaming. IEEE Trans. Multimedia 8, 6, 1135--1146.

Digital Library

[9]

Ding, W. and Liu, B. 1996. Rate control of MPEG video coding and recording by rate-quantization modeling. IEEE Trans. Circ. Syst. Video Techn. 6, 1, 12--20.

Digital Library

[10]

Hang, H. and Chen, J. 1997. Source model for transform video coder and its application I: Fundamental theory. IEEE Trans. Circ. Syst. Video Techn. 7, 2, 287--298.

Digital Library

[11]

He, Z., Kim, Y., and Mitra, S. 2001. Low-delay rate control for DCT video coding via ρ-domain source modeling. IEEE Trans. Circ. Syst. Video Techn. 11, 8, 928--940.

Digital Library

[12]

He, Z. and Mitra, S. 2001. A unified rate-distortion analysis framework for transform coding. IEEE Trans. Circ. Syst. Video Techn. 11, 12, 1221--1236.

Digital Library

[13]

He, Z. and Mitra, S. 2002. A linear source model and a unified rate control algorithm for DCT video coding. IEEE Trans. Circ. Syst. Video Techn. 12, 11, 970--982.

Digital Library

[14]

Hsu, C. and Hefeeda, M. 2006a. On the accuracy and complexity of rate-distortion models for fine-grained scalable video sequences. Tech. rep. TR 2006-12, Simon Fraser University. http://nsl.cs.surrey.sfu.ca/projects/fgs/.

[15]

Hsu, C. and Hefeeda, M. 2006b. Source models for fine-grained scalable video sequences. Tech. rep., Simon Fraser University.

[16]

ISO/IEC 14496-2. 2004. Coding of audio-visual objects—part 2: Visual.

[17]

ISO/IEC 14496-5. 2004. MPEG-4 Visual reference software.

[18]

Joshi, R. and Fischer, T. 1995. Comparison of generalized Gaussian and Laplacian modeling in DCT image coding. IEEE Signal Proces. Lett. 2, 5, 81--82.

[19]

Li, W. 2001. Overview of fine-granularity scalability in MPEG-4 video standard. IEEE Trans. Circ. Syst. Video Techn. 11, 3, 301--317.

Digital Library

[20]

Lin, L. and Ortega, A. 1998. Bit-rate control using piecewise approximated rate-distortion characteristics. IEEE Trans. Circ. Syst. Video Techn. 8, 4, 446--459.

Digital Library

[21]

Mallet, S. and Falzon, F. 1998. Analysis of low bit rate image transform coding. IEEE Trans. Signal Process. 46, 4, 1027--1042.

Digital Library

[22]

Martinez, W. and Martinez, A. 2002. Computational Statistics Handbook with Matlab, 1st ed. Chapman and Hall, Upper Saddle River, NJ.

Digital Library

[23]

Muller, F. 1993. Distribution shape of two-dimensional DCT coefficients of natural images. IEEE Electron. Lett. 29, 22, 1935--1936.

[24]

Park, H. J. and Lee, T. W. 2004. Modeling nonlinear dependencies in natural images using mixture of Laplacian distribution. In Proceedings of Advances in Neural Information Processing Systems (NIPS'04). Vancouver, Canada.

[25]

Radha, H., Schaar, M., and Chen, Y. 2001. The MPEG-4 fine-grained scalable video coding method for multimedia streaming over IP. IEEE Trans. Multimedia 3, 1, 53--68.

Digital Library

[26]

Sullivan, G. and Wiegand, T. 1998. Rate-distortion optimization for video compression. IEEE Signal Process. Magazine 15, 6, 74--90.

[27]

Sun, J., Gao, W., Zhao, D., and Huang, Q. 2005. Statistical model, analysis and approximation of rate-distortion function in MPEG-4 FGS videos. In Proceedings of SPIE International Conference on Visual Communication and Image Processing (VCIP'05). Beijing, China.

[28]

Varanasi, M. and Aazhang, B. 1989. Parametric generalized Gaussian density estimation. J. Acoust. Soc. Amer. 86, 4, 1404--1415.

[29]

Video Traces Research Group. 2006. http://trace.eas.asu.edu/yuv.

[30]

Zhang, X., Vetro, A., Shi, Y., and Sun, H. 2003. Constant quality constrained rate allocation for FGS-coded video. IEEE Trans. Circ. Syst. Video Techn. 13, 2, 121--130.

Digital Library

Cited By

Shen LAn PFeng G(2019)Low-Complexity Scalable Extension of the High-Efficiency Video Coding (SHVC) Encoding SystemACM Transactions on Multimedia Computing, Communications, and Applications10.1145/331318515:2(1-23)Online publication date: 5-Jun-2019
https://dl.acm.org/doi/10.1145/3313185
Do NHsu CVenkatasubramanian N(2014)Video Dissemination over Hybrid Cellular and Ad Hoc NetworksIEEE Transactions on Mobile Computing10.1109/TMC.2012.24613:2(274-286)Online publication date: 1-Feb-2014
https://dl.acm.org/doi/10.1109/TMC.2012.246
Xie MWei GGe YLing Y(2012)Receiving-peer-driven multi-video-source scheduling algorithms in mobile P2P overlay networksComputers and Electrical Engineering10.1016/j.compeleceng.2011.10.00738:1(116-127)Online publication date: 1-Jan-2012
https://dl.acm.org/doi/10.1016/j.compeleceng.2011.10.007
Show More Cited By

Index Terms

On the accuracy and complexity of rate-distortion models for fine-grained scalable video sequences
1. Computing methodologies
  1. Modeling and simulation
    1. Simulation theory
      1. Systems theory
2. Mathematics of computing
  1. Information theory

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Published In

cover image ACM Transactions on Multimedia Computing, Communications, and Applications

ACM Transactions on Multimedia Computing, Communications, and Applications Volume 4, Issue 2

May 2008

197 pages

ISSN:1551-6857

EISSN:1551-6865

DOI:10.1145/1352012

Issue’s Table of Contents

Copyright © 2008 ACM.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 May 2008

Accepted: 01 February 2007

Revised: 01 December 2006

Received: 01 August 2006

Published in TOMM Volume 4, Issue 2

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Cited By

Shen LAn PFeng G(2019)Low-Complexity Scalable Extension of the High-Efficiency Video Coding (SHVC) Encoding SystemACM Transactions on Multimedia Computing, Communications, and Applications10.1145/331318515:2(1-23)Online publication date: 5-Jun-2019
https://dl.acm.org/doi/10.1145/3313185
Do NHsu CVenkatasubramanian N(2014)Video Dissemination over Hybrid Cellular and Ad Hoc NetworksIEEE Transactions on Mobile Computing10.1109/TMC.2012.24613:2(274-286)Online publication date: 1-Feb-2014
https://dl.acm.org/doi/10.1109/TMC.2012.246
Xie MWei GGe YLing Y(2012)Receiving-peer-driven multi-video-source scheduling algorithms in mobile P2P overlay networksComputers and Electrical Engineering10.1016/j.compeleceng.2011.10.00738:1(116-127)Online publication date: 1-Jan-2012
https://dl.acm.org/doi/10.1016/j.compeleceng.2011.10.007
Liu SChen CKrasic CLi K(2011)Scalable video transmissionProceedings of the 21st international workshop on Network and operating systems support for digital audio and video10.1145/1989240.1989268(111-116)Online publication date: 1-Jun-2011
https://dl.acm.org/doi/10.1145/1989240.1989268
Hossain TCui YXue Y(2009)Rate distortion optimization for mesh-based P2P video streamingProceedings of the 2009 IEEE international conference on Communications10.5555/1817271.1817538(1436-1441)Online publication date: 14-Jun-2009
https://dl.acm.org/doi/10.5555/1817271.1817538
Xie M(2009)Multi-Video-Sources Selection Strategy in Mobile P2P Streaming Media ArchitectureInformation Technology Journal10.3923/itj.2009.863.8708:6(863-870)Online publication date: 1-Jun-2009
https://doi.org/10.3923/itj.2009.863.870
Maani EKatsaggelos A(2009)Optimized bit extraction using distortion modeling in the scalable extension of H.264/AVCIEEE Transactions on Image Processing10.1109/TIP.2009.202315218:9(2022-2029)Online publication date: 1-Sep-2009
https://dl.acm.org/doi/10.1109/TIP.2009.2023152
Hossain TCui YXue Y(2009)Rate Distortion Optimization for Mesh-Based P2P Video Streaming2009 IEEE International Conference on Communications10.1109/ICC.2009.5199392(1-6)Online publication date: Jun-2009
https://doi.org/10.1109/ICC.2009.5199392
Hsu CHefeeda MEL Saddik AVuong SGriwodz CDel Bimbo ACandan KJaimes A(2008)Video communication systems with heterogeneous clientsProceedings of the 16th ACM international conference on Multimedia10.1145/1459359.1459569(1043-1046)Online publication date: 26-Oct-2008
https://dl.acm.org/doi/10.1145/1459359.1459569

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