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IEEE Journal on Selected Areas in Communications
Volume 15 Number 9, December 1997

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Spatially Scalable Video Compression Employing Resolution Pyramids

Klaus Illgner and Frank Müller

Page 1688.

Abstract:

In this paper, a spatially scalable video coding scheme for low bit rates is proposed. The codec is especially well suited for communications applications because it is based on motion-compensated predictive coding which provides the necessary low-delay property. The frames to be coded are decomposed into a Gaussian pyramid. Motion estimation and compensation are performed between corresponding pyramid levels of successive frames. We show that, to fulfill specific needs of spatial scalability, the motion compensation on each level must result in compatible prediction errors (displaced frame differences, DFD). Compatibility of the prediction errors means that the pyramid formed by independently obtained DFD's (the DFD pyramid) is close to a Gaussian pyramid decomposition of the DFD of the highest resolution level. From the DFD pyramid, a least squares Laplacian pyramid is derived, which is quantized and coded. The DFD encoder outputs an embedded bit stream. Thus, the coder control may truncate the bit stream at any point, and can keep a fixed rate. The motion vector fields obtained at the different resolution levels are also encoded by employing a pyramid approach. Simulation results show that the proposed coder achieves a coding gain compared to simulcast coding.

References

  1. T. Hanamura, W. Kameyama, and H. Tominaga, "Hierarchical coding scheme of video signals with scalability and compatibility," Signal Processing: Image Commun., vol. 5, pp. 159-184, Feb. 1993.
  2. B. Girod, U. Horn, and B. Belzer, "Scalable video coding with multiscale motion compensation and unequal error protection," in Proc. Symp. Multimedia Communication Video Coding, New York, NY, Oct. 1995.
  3. P.-Y. Cheng, J. Li, and C.-C. Jay Kuo, "Multiscale video compression using wavelet transform and motion compensation," in Proc. IEEE Int. Conf. Image Processing, vol. I, Washington DC, 1995, pp. 606-609.
  4. T. Naveen and J. W. Woods, "Motion compensated multiresolution transmission of high definition video," IEEE Trans. Circuits Syst. Video Technol., vol. 4, pp. 29-41, Feb. 1994.
  5. K. Tsunashima, J. B. Stampleman, and V. M. Bove, "A scalable motion-compensated subband image coder," IEEE Trans. Commun., vol. 42, pp. 1894-1901, Feb./Mar./Apr. 1994.
  6. J. M. Shapiro, "Embedded image coding using zerotrees of wavelet coefficients," IEEE Trans. Signal Processing, vol. 41, pp. 3445-3462, Dec. 1993.
  7. D. Taubmann and A. Zakhor, "Multirate 3-D subband coding of video," IEEE Trans. Image Processing, vol. 3, pp. 572-588, Sept. 1994.
  8. F. Müller, K. Illgner, and B. Menser, "Embedded Laplacian pyramid image coding using conditional arithmetic coding," in Proc. IEEE Int. Conf. Image Processing, ICIP'96, vol. I, Lausanne, Switzerland, Sept. 1996, pp. 221-224.
  9. M. Unser, A. Aldroubi, and M. Eden, "B-spline signal processing: Part II--Efficient design and applications," IEEE Trans. Signal Processing, vol. 41, pp. 834-848, May 1993.
  10. K. Illgner and F. Müller, "Hierarchical coding of motion vector fields," in Proc. IEEE Int. Conf. Image Processing, ICIP'95, vol. I, Washington DC, Oct. 1995, pp. 566-569.
  11. ITU-T International Telecommunication Union, Draft ITU-T Recommendation H.263 (Video Coding for Low Bitrate Communication), KPN Research, The Netherlands, Jan. 1995.
  12. P. J. Burt and E. H. Adelson, "The Laplacian pyramid as a compact image code," IEEE Trans. Commun., vol. COM-31, pp. 532-540, Apr. 1983.
  13. O. Werner, "Drift analysis and drift reduction for multiresolution video coding," Signal Processing: Image Commun., vol. 8, pp. 387-409, May 1996.
  14. B. Girod, "Motion compensation: Visual aspects, accuracy, and fundamental limits," in Motion Analysis and Image Sequence Processing, M. I. Sezan and R. L. Lagendijk, Eds.Boston: Kluwer Academic, 1993, pp. 125-152.
  15. M. Unser, A. Aldroubi, and M. Eden, "B-spline signal processing: Part I--Theory," IEEE Trans. Signal Processing, vol. 41, pp. 821-833, May 1993.
  16. K. Illgner and F. Müller, "Motion estimation using overlapped block motion compensation and Gibbs-modeled vector fields," in Proc. 9th Workshop Image and Multidimensional Signal Processing (IMDSP'96), Belize City, Belize, Mar. 1996, pp. 126-127.
  17. J. Rissanen and G. G. Langdon, "Universal modeling and coding," IEEE Trans. Inform. Theory, vol. IT-27, pp. 12-23, Jan. 1981.
  18. I. H. Witten, R. M. Neal, and J. G. Cleary, "Arithmetic coding for data compression," Commun. ACM, vol. 30, pp. 520-540, June 1987.
  19. G. Strang and T. Nguyen, Wavelets and Filter Banks.Wellesley-Cambridge Press, 1996.
  20. M. Unser, "Approximation power of biorthogonal wavelet expansions," IEEE Trans. Signal Processing, vol. 44, pp. 519-527, Mar. 1996.
  21. A. Aldroubi, M. Unser, and M. Eden, "Cardinal spline filters: Stability and convergence to the ideal sinc interpolator," Signal Processing, vol. 28, pp. 127-138, 1992.