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Design Techniques and Implementation of Low Power High-Throughput Discrete Wavelet Transform Tilters for JPEG 2000 Standard

Authors: Grigorios D. Dimitroulakos, N. D. Zervas, N. Sklavos, Costas E. Goutis

Abstract:

In this paper, the implementation of low power, high throughput convolutional filters for the one dimensional Discrete Wavelet Transform and its inverse are presented. The analysis filters have already been used for the implementation of a high performance DWT encoder [15] with minimum memory requirements for the JPEG 2000 standard. This paper presents the design techniques and the implementation of the convolutional filters included in the JPEG2000 standard for the forward and inverse DWT for achieving low-power operation, high performance and reduced memory accesses. Moreover, they have the ability of performing progressive computations so as to minimize the buffering between the decomposition and reconstruction phases. The experimental results illustrate the filters- low power high throughput characteristics as well as their memory efficient operation.

Keywords: Discrete Wavelet Transform; JPEG2000 standard; VLSI design; Low Power-Throughput-optimized filters

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1062444

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References:


[1] I. Daubechies, "Ten Lectures on Wavelets," CBMS-NSF Series in Applied Mathematics, 61, SIAM, Philadelphia, 1992.
[2] Munteanu, J. Cornelis, G. V. der Auwera, P. Cristea, "Wavelet based lossless compression scheme with progressive transmission capability," International Journal of Imaging Systems and Technology, vol. 10, pp. 76-85, January 1999.
[3] Said and W. A. Pearlman, "A new fast and efficient image codec based on set partitioning in hierarchical trees," IEEE Trans. Circuits and Syst. Video Technol., vol. 6, pp. 243-250, June 1996.
[4] J. M. Shapiro, "Embedded image coding using zerotrees of wavelet coefficients," IEEE Trans. On Signal Processing, vol. 41, pp. 3445- 3462, Dec. 1993.
[5] JPEG 2000 Image Coding System, ISO/IEC FCD15444-1, 2000.
[6] MPEG-4, ISO/IEC JTC1/SC29/WG11, FCD 14496, "Coding of Moving Pictures and Audio," May 1998.
[7] C. Chakrabarti and M. Vishwanath, "Efficient realizations of the discrete and continuous wavelet transforms: from single chip implementations to SIMD parallel computers," IEEE Trans. Signal Processing, vol. 43, no.3, pp. 759-771, March 1995.
[8] C. Chakrabarti and M. Vishwanath and R. M. Owens, "Architectures for wavelet transforms: A survey," Journal of VLSI Signal Processing, vol. 4, no. 2, pp 171-192, 1996.
[9] Vishwanath, R. M. Owens, M. J. Irwin "VLSI architectures for the discrete wavelet transform", IEEE Trans. Circuits and Syst. II, vol. 42, no. 5, May 1995.
[10] N. D. Zervas, G. P. Anagnostopoulos, V. Spiliotopoulos, Y. Andreopoulos and C.E. Goutis, "Evaluation of design alternatives for the 2-D-discrete wavelet transform", IEEE Trans. Circuits and Syst. Video Technol., vol. 11, no. 2, pp. 1246-1262, December 2001.
[11] F. Catthoor, S. Wuytack, E. De Greff, F. Balasa, L.Nachtergale, A. Vandecappele, "Custom Memory Management Methodology - Exploration of Memory management Organization for Embedded Multimedia System Design", Kluwer Academic Publishers, 1998.
[12] S. Mallat, "A Wavelet Tour of Signal Processing", 2nd Edition.
[13] A. Skodras, C. Christopoulos, T. Ebrahimi, "The JPEG 2000 still image compression standard", in IEEE Signal Processing Magazine, vol. 18, no. 5, pp. 36-58, Sept. 2001.
[14] G. Lafruit, L. Nachtergale, J. Bormans, M. Engels, I. Bolsens, "Optimal memory organizations for scalable texture codecs in MPEG-4", IEEE Trans. Circuits and Syst. Video Technol., vol. 9, no. 2, pp. 218-242, March 1999.
[15] G. Dimitroulakos, M. D. Galanis, A. Milidonis and C.E. Goutis, "A high- throughput memory efficient architecture for computing the tilebased 2D Discrete Wavelet Transform for the JPEG 2000 Standard", Integration the VLSI Journal, Elsevier Publishers, vol. 39, no. 1, pp. 1- 11, 2005.
[16] C. Chakrabarti and C. Mumford, "Efficient realizations of analysis and synthesis filters based on the 2-D discrete wavelet transform," in Proc. Int. Conf. On Acoustics, Speech and Signal processing, pp. 3256-3259, May 1996.
[17] F. Fridman and E. S. Manolakos, "Distributed memory and control VLSI architectures for the 1-D discrete wavelet transform," in IEEE VLSI Signal Processing VII, pp. 388-397, 1994.
[18] Grzeszczak, M. K. Mandal, S. Panchanathan, and T. Yeap, "VLSI implementation of discrete wavelet transform," IEEE Trans. VLSI Syst., vol. 4, pp. 421-433, Dec. 1996.
[19] G. Knowles, "VLSI architecture for the discrete wavelet transform", Electronic Letters, vol. 26, no.5, pp. 1184-1185, July 1990.
[20] R. Lang, E. Plesner, H. Schroder, and A. Spray, "An efficient systolic architecture for the one-dimensional wavelet transform," in Proc. SPIE Conf. Wavelet Applicat., pp. 925-935, April 1994.
[21] A. S. Lewis and G. Knowles, "VLSI architecture for 2-D Daubechies wavelet transform without multipliers," Electronic Letters, vol. 27, no.5, pp. 171-173, Jan 1991.
[22] C.M. Brislawn, "Classification of nonexpansive symmetric extension transforms for multirate filter banks" Tech. Rep. LA-UR-94-1747, Los Alamos, Nat. Laboratory, May 1994.
[23] T. Denk and K. Parhi, "Calculation of minimum number of registers in 2-D discrete wavelet transforms using lapped block processing," in Proc. Int. Symp. Circuits Syst., pp. 77-81, 1994.