Abstract
The richness of wavelet transform has been known in many fields. There exist different classes of wavelet filters that can be used depending on the application. In this chapter, we propose a general purpose lifting-based wavelet processor that can perform various forward and inverse DWTs. Our architecture is based on M processing elements (PEs) that can perform either prediction or update on a continuous data stream in every clock cycle. We also consider the normalization step that takes place at the end of the forward DWT or at the beginning of the inverse DWT. To cope with different wavelet filters and different applications, we feature a multi-context configuration to select among various DWTs and an arbitrary memory size to compute the transform. For the 16-bit implementation, the estimated area of the proposed wavelet processor with 8 PEs and 2x512 words memory in a 0.18-μm technology is 2.3 mm square and the estimated frequency is 347 MHz.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Agbinya, J.: Discrete wavelet transform techniques in speech processing. In: Proc. of the IEEE TENCON. Digital Signal Processing Applications, TENCON 1996, vol. 2, pp. 514–519 (1996)
Andra, K., Chakrabarti, C., Acharya, T.: A VLSI architecture for lifting-based forward and inverse wavelet transform 50(4), 966–977 (2002)
Barua, S., Carletta, J., Kotteri, K., Bell, A.: An Efficient Architecture for Lifting-based Two-Dimensional Discrete Wavelet Transforms. In: Proc. of the GLSVLSI 2004 (2004)
Bultheel, A.: Wavelets with applications in signal and image processing (2003)
Calderbank, R., Daubechies, I., Sweldens, W., Yeo, B.-L.: Lossless image compression using integer to integer wavelet transforms. In: Proc. of the International Conference on Image Processing (ICIP), vol. 1, pp. 596–599. IEEE Press, Los Alamitos (1997)
Carnero, B., Drygajlo, A.: Perceptual speech coding and enhancement using frame-synchronized fast wavelet packet transform algorithms 47, 1622–1634 (1999)
Christopoulos, C., Skodras, A., Ebrahimi, T.: The JPEG 2000 still image coding system: An overview 46(4), 1103–1127 (2000)
Daubechies, I.: The wavelet transform, time-frequency localization and signal analysis. IEEE Transactions on Information Theory 36, 961–1005 (1990)
Daubechies, I., Sweldens, W.: Factoring Wavelet Transforms into Lifting Steps. J. Fourier Anal. Appl. 4(3), 245–267 (1998)
Dillen, G., Georis, B., Legat, J., Cantineau, O.: Combined line-based architecture for the 5-3 and 9-7 wavelet transform of JPEG 2000 13(9), 944–950 (2003)
Grgic, S., Kers, K., Grgic, M.: Image compression using wavelets. In: Proc. of the IEEE International Symposium on Industrial Electronics ISIE 1999, vol. 1 (1999)
Kaisheng, Y., Zhigang, C.: A wavelet filter optimization algorithm for speech recognition. In: Proc. of the Intl. Conference on Communication Technology, ICCT 1998, October 22-24, vol. 2 (1998)
Mallat, S. (ed.): A Wavelet Tour of Signal Processing. Academic Press, New York (1998) (Incorporated)
Martina, M., Masera, G., Piccinini, G., Zamboni, M.: A VLSI architecture for IWT (Integer wavelet Transform). In: Proc. of the 43rd IEEE Midwest Symposium on Circuits and Systems, vol. 3 (2000)
Meyer, Y.: Wavelets and Operators. Press Syndicate of the University of Cambridge (1992)
Seo, Y.-H., Kim, D.-W.: A New VLSI Architecture of Lifting-Based DWT. In: Bertels, K., Cardoso, J.M.P., Vassiliadis, S. (eds.) ARC 2006. LNCS, vol. 3985, pp. 146–151. Springer, Heidelberg (2006)
Sweldens, W.: The Lifting Scheme: A New Philosophy in Biorthogonal Wavelet Constructions. Wavelet Applications in Signal and Image Processing 3, 68–79 (1995)
Usevitch, B.: A tutorial on modern lossy wavelet image compression: foundations of JPEG 2000 18(5), 22–35 (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Guntoro, A., Keil, HP., Glesner, M. (2009). High-Speed Configurable VLSI Architecture of a General Purpose Lifting-Based Discrete Wavelet Processor. In: Filipe, J., Obaidat, M.S. (eds) e-Business and Telecommunications. ICETE 2008. Communications in Computer and Information Science, vol 48. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05197-5_23
Download citation
DOI: https://doi.org/10.1007/978-3-642-05197-5_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-05196-8
Online ISBN: 978-3-642-05197-5
eBook Packages: Computer ScienceComputer Science (R0)