Implementation of the Wavelet Transform with SSE Extensions

• Autorzy: Łyszkowski T. , Wiechno T. , Yatsymirskyy M.
• Języki publikacji: EN

Abstrakty

EN

It has been shown that application of assembly implementation of Streaming SIMD Extensions (SSE) shortens the time needed to apply filtration in twochannel filter bank by tenfold, comparing to non-optimized version, written in Microsoft Visual C++ 2010 Express, without assembler extensions. The implementation described in this paper can be applied to computation of Discrete Wavelet Transform on general-purpose processors.

Słowa kluczowe

EN

orthogonal filters; discrete wavelet transform; SSE extensions

• Wydawca: Społeczna Akademia Nauk w Łodzi
• Czasopismo: Journal of Applied Computer Science Methods
• Rocznik: 2013
• Tom: Vol. 5 No. 2
• Strony: 123--135
• Opis fizyczny: Bibliogr. 14 poz., rys., tab.

Twórcy

autor

Łyszkowski T.

• Higher Vocational State School in Wloclawek

autor

Wiechno T.

• Institute of Information Technology, Lodz University of Technology

autor

Yatsymirskyy M.

• Institute of Information Technology, Lodz University of Technology

Bibliografia

• 1. Zieliński T. P.,2009,Cyfrowe przetwarzanie sygnałów. Od teorii do zastosowań, WKŁ, Warszawa
• 2. Fleet P. J.: 2008, Discrete wavelet transformations: An elementary Approach with applications, John Wiley&Sons, New Jersey.
• 3. Strang G., Nguyen T., 1999,Wavelets and filter banks, Wellesley-Cambridge Press.
• 4. Lipiński P.,2011,Watermarking software in practical applications, Bulletin of Polish Academy of Sciences: Technical Sciences, Vol. 59, nr 1, pp. 21-25.
• 5. Cooklev T., 2006,An efficient architecture for orthogonal wavelet transforms, IEEE Signal processing letters, Vol. 13, nr 2, pp. 77-79.
• 6. Olkkonen J. T., Olkkonen H., 2007,Discrete lattice wavelet transform, IEEE Transactions on circuits and systems II: Express briefs, Vol. 54, nr 1, pp. 71-75.
• 7. Daubechies I., Sweldens W., 1998,Factoring Wavelet Transform into Lifting Steps, The Journal of Fourier Analysis and Applications, Vol. 4, nr 3, pp. 245-267.
• 8. Denk T. C., Parhi K. K., 1997,VLSI architectures for lattice structure based orthonormal discrete wavelet transforms, IEEE Transactions on circuits and systems II: Analog and digital signal processing, Vol. 44, nr 2, pp. 129-132.
• 9. Bernabe G., Garcia J. M., Gonzalez J., 2003,Reducing 3D Wavelet Transform Execution Time through the Streaming SIMD Extensions, IEEE Computer Society, Proceedings of the Eleventh Euromicro Conference on Parallel, Distributed and Network-Based Processing, pp. 209-223
• 10. ShahbahramiA., Juurlink B., Vassiliadis S., 2008,Implementing the 2-D Wavelet Transform on SIMD-Enhanced General-Purpose processors, IEEE Transactions on multimedia, Vol. 10, nr 1, pp. 43-51.
• 11. Yatsymirskyy M., 2011,Nowy model macierzowy dwukanałowego banku biortogonalnych filtrów, Metody Informatyki Stosowanej, nr 1/2011 (26), Polska Akademia Nauk Oddział w Gdańsku, Komisja Informatyki, pp. 205-212.
• 12. Yatsymirskyy M.,Stokfiszewski K., 2012, Effectiveness of Lattice Factorization of Two-Channel Orthogonal Filter Banks, New Trends in Audio and Video/Signal Processing Algorithms, Architectures, Arrangements and Applications, 27-29 September, Łódź, pp. 275-279.
• 13. Intel® 64 and IA-32 Architectures. Software Developer's Manual, Volume 1: Basic Architecture.
• 14. Gomersall H., 2012, Speedy fast 1D convolution with SSE, http://hgomersall.wordpress.com/2012/11/02/speedy-fast-1d-convolution-withsse/