A Comparison of Folded Architectures for the Discrete Wavelet Transform

  • Jia Zhou
  • Jiang Jiang
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 337)


The multi-level discrete wavelet transform (DWT) for multiresolution decomposition of a signal through the cascading of filter banks, employs a folded architecture to enhance hardware utilization. This work compares folded architectures for DWT based on three filter structures, the direct form filter, the linear systolic array, and the lifting structure. We generalize the design of these architectures in terms of DWT levels, filter taps and pipeline insertion in critical path. A figure of merit for assessing all the three architectures under different specifications is proposed. A detailed quantitative comparison among the architectures is presented with different combinations of specification. The result shows that variations in DWT levels, filter taps and pipeline insertions have different impacts on the three architectures. Overall, the folded architecture based on lifting structure gives the most desirable figure of merit and the one based on linear systolic array demonstrates the best scalability.


VLSI Discrete Wavelet Transform Multiresolution Decomposition 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Christopoulos, C., Skodras, A., Ebrahimi, T.: The JPEG2000 still image coding system: an overview. IEEE Transactions on Consumer Electronics 46(4), 1103–1127 (2000), doi:10.1109/30.920468CrossRefGoogle Scholar
  2. 2.
    Chung-Jr, L., Kuan-Fu, C., Hong-Hui, C., Liang-Gee, C.: Lifting based discrete wavelet transform architecture for JPEG2000. In: The 2001 IEEE International Symposium on Circuits and Systems, ISCAS 2001, May 6-9, vol. 442, pp. 445–448 (2001), doi:10.1109/iscas.2001.921103Google Scholar
  3. 3.
    Goupillaud, P., Grossmann, A., Morlet, J.: Cycle-octave and related transforms in seismic signal analysis. Geoexploration 23(1), 85–102 (1984), doi:10.1016/0016-7142(84)90025-5CrossRefGoogle Scholar
  4. 4.
    Vetterli, M., Herley, C.: Wavelets and Filter Banks: Theory and Design. IEEE Trans., Signal Processing 40(9), 2207–2232 (1992)zbMATHCrossRefGoogle Scholar
  5. 5.
    Mallat, S.G.: Multifrequency channel decompositions of images and wavelet models. IEEE Transactions on Acoustics, Speech and Signal Processing 37(12), 2091–2110 (1989), doi:10.1109/29.45554CrossRefGoogle Scholar
  6. 6.
    Meyer, Y.: Wavelets and Applications: Proceedings of the International Conference, Marseille, France, Masson. Recherches en mathématiques appliquées = Research notes in applied mathematics, vol. 20. Springer, Paris (1989)Google Scholar
  7. 7.
    Parhi, K.K.: Systematic synthesis of DSP data format converters using life-time analysis and forward-backward register allocation. IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing 39(7), 423–440 (1992), doi:10.1109/82.160168CrossRefGoogle Scholar
  8. 8.
    Parhi, K.K., Nishitani, T.: VLSI architectures for discrete wavelet transforms. IEEE Transactions on Very Large Scale Integration (VLSI) Systems 1(2), 191–202 (1993), doi:10.1109/92.238416CrossRefGoogle Scholar
  9. 9.
    Sweldens, W.: The lifting scheme: A custom-design construction of biorthogonal wavelets. Appl. Comput. Harmon. Anal. 3(2), 14 (1996)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Vishwanath, M.: The recursive pyramid algorithm for the discrete wavelet transform. IEEE Transactions on Signal Processing 42(3), 673–676 (1994), doi:10.1109/78.277863CrossRefGoogle Scholar
  11. 11.
    Vishwanath, M., Owens, R.M., Irwin, M.J.: VLSI architectures for the discrete wavelet transform. IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing 42(5), 305–316 (1995), doi:10.1109/82.386170zbMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Jia Zhou
    • 1
  • Jiang Jiang
    • 1
  1. 1.School of MicroelectronicsShanghai Jiao Tong UniversityChina

Personalised recommendations