Abstract
With the start of the widespread use of discrete wavelet transform the need for its effective implementation is becoming increasingly more important. This work presents a novel approach to discrete wavelet transform through a new computational scheme of wavelet lifting. The presented approach is compared with two other. The results are obtained on a general purpose processor with 4-fold SIMD instruction set (such as Intel x86-64 processors). Using the frequently exploited CDF 9/7 wavelet, the achieved speedup is about 3× compared to naive implementation.
The original version of this chapter was revised: The copyright line was incorrect. This has been corrected. The Erratum to this chapter is available at DOI: 10.1007/978-3-319-02895-8_64
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References
Adams, M.D.: Reversible integer-to-integer wavelet transforms for image coding. Ph.D. thesis, Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada (September 2002)
Chrysafis, C., Ortega, A.: Line-based, reduced memory, wavelet image compression. IEEE Transactions on Image Processing 9(3), 378–389 (2000)
Chrysafis, C., Ortega, A.: Minimum memory implementations of the lifting scheme. In: Proceedings of SPIE, Wavelet Applications in Signal and Image Processing VIII. SPIE, vol. 4119, pp. 313–324 (2000)
Cohen, A., Daubechies, I., Feauveau, J.C.: Biorthogonal bases of compactly supported wavelets. Communications on Pure and Applied Mathematics 45(5), 485–560 (1992)
Daubechies, I., Sweldens, W.: Factoring wavelet transforms into lifting steps. Journal of Fourier Analysis and Applications 4(3), 247–269 (1998)
Kutil, R.: A single-loop approach to SIMD parallelization of 2-D wavelet lifting. In: Proceedings of the 14th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP), pp. 413–420 (2006)
Kutil, R., Eder, P., Watzl, M.: SIMD parallelization of common wavelet filters. In: Parallel Numerics 2005, pp. 141–149 (2005)
Mallat, S.: A Wavelet Tour of Signal Processing: The Sparse Way. With contributions from Gabriel Peyré, 3rd edn. Academic Press (2009)
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Barina, D., Zemcik, P. (2013). Minimum Memory Vectorisation of Wavelet Lifting. In: Blanc-Talon, J., Kasinski, A., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2013. Lecture Notes in Computer Science, vol 8192. Springer, Cham. https://doi.org/10.1007/978-3-319-02895-8_9
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DOI: https://doi.org/10.1007/978-3-319-02895-8_9
Publisher Name: Springer, Cham
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