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Further improvement on dynamic programming for optimal bit allocation

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Abstract

Dynamic programming algorithms based on Lagrange multiplier method is often used for obtaining an optimal bit allocation strategy to minimize the total distortion given a constrained rate budget in both source and channel coding applications. Due to possible large quantizer set and improper initialization, the algorithm often suffers from heavy computational complexity. There have been many solutions in recent years to the above question. In this paper, a simple but efficient algorithm is presented to further speed up the convergence of the algorithm. This algorithm can be easily realized and get the final solution much faster. The experimental result shows that our new algorithm can figure out the optimal solution with a speed 5–7 times faster than the original algorithm.

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References

  1. Shoham Y, Gersho A. Efficient bit allocation for an arbitrary set of quantizers.IEEE Transactions on Acoustics, Speech, and Signal Processing, 1988, 36(9): 1445–1453.

    Article  MATH  Google Scholar 

  2. Chen Jet al. Optimal bit allocation for coding of video signals over ATM network.IEEE Journal on Selected Areas in Communications, Aug., 1997, 15(6): 1002–1025.

    Article  Google Scholar 

  3. Schuster G, Melnikov G, Katsaggelos A. A review of the minimum maximum criterion for optimal bit allocation among dependent quantizers.IEEE Transactions on Multimedia, March, 1999, 1(1): 3–17.

    Article  Google Scholar 

  4. Westerink P, Biemond J, Boekee D. An optimal bit allocation algorithm for sub-band coding. InProc. IEEE ICASSP88, New York, April, 1988, Vol.2, pp.757–760.

  5. Ronda Jet al. Rate control and bit allocation for MPEG-4.IEEE Trans. Circuits and Systems for Video Technology, December, 1999, 9(8): 1243–1258.

    Article  Google Scholar 

  6. Cheung C, Zakhor A. Bit allocation for joint source/channel coding of scalable video.IEEE Trans. Image Processing, March, 2000, 9(3): 340–356.

    Article  Google Scholar 

  7. Gray R M. Source Coding Theory. Norwell, MA: Kluwer Academic Press, 1990.

    MATH  Google Scholar 

  8. Chou P, Lookabaugh T, Gray R. Optimal pruning with applications to tree-structured source coding and modeling.IEEE Trans. Information Theory, March, 1989, IT-35: 299–315.

    Article  MathSciNet  Google Scholar 

  9. Ramchandran K, Vetterli M. Best wavelet packet bases in a rate-distortion sense.IEEE Trans. Image Processing, April, 1993, 2(2): 160–175.

    Article  Google Scholar 

  10. Ramchandran K, Ortega A, Vetterli M. Bit allocation for dependent quantization with applications to multiresolution and MPEG video coders.IEEE Trans. Image Processing, September, 1994, 3(4): 533–545.

    Article  Google Scholar 

  11. Ortega A. Optimal bit allocation under multiple rate constraints. InProc. IEEE DCC'96, 1996, pp.349–358.

  12. Geoff Davis. Baseline wavelet transform coder construction kit. Technical Report, University of Dartmouth, January, 1997.

  13. Riskin E. Optimal bit allocation via the generalized BFOS algorithm.IEEE Trans. Information Theory, March, 1991, 37(2): 400–402.

    Article  MathSciNet  Google Scholar 

  14. LEE W, Ra J. Fast algorithm for optimal allocation in a rate-distortion sense.Electronics Letters, September, 1996, 32(20): 1871–1873.

    Article  Google Scholar 

  15. Lynch T J. Data Compression Techniques and Applications. Lifetime Learning Publications, Belmont, CA, 1985.

    Google Scholar 

  16. Gersho Aet al. Vector Quantization and Signal Compression. Boston, MA: Kluwer Academic Press, 1992.

    MATH  Google Scholar 

Download references

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Correspondence to Chen YiSong.

Additional information

This work is supported by the National Natural Science Foundation of China (Grant No.60033020).

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Chen, Y., Wang, G. & Dong, S. Further improvement on dynamic programming for optimal bit allocation. J. Comput. Sci. & Technol. 18, 109–113 (2003). https://doi.org/10.1007/BF02946658

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  • DOI: https://doi.org/10.1007/BF02946658

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