International Journal of Information Technology and Computer Science (IJITCS)
IJITCS Vol. 2, No. 2, 8 Dec. 2010
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An Improved Wavelet Filtering Algorithm and Its FPGA Implementation
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Author(s)
Lan Yang
1,*
Xiang-mo Zhao
2
Fei Hui
2
Xin Shi
2
Index Terms
FPGA implementation, Wavelet Threshold Filtering, Digital Signal Process
Abstract
The de-noising of sensor data has become an important to research. Since the traditional de-noising method can’t achieve successful de-noising effect and the software-only method never meets a high real time capability. In this paper, we illustrate a novel threshold function based on the wavelet hard and soft threshold function. It is unlike ordinary function, which has overcome the defect such as the discontinuity of hard threshold function and an invariable dispersion between the estimated wavelet coefficients and the decomposed coefficients of soft threshold function. Moreover, we consider the hardware implementation of wavelet threshold filter on FPGA which adopt the pleated sheet structure of multiplier and fit to frame data. A detailed description of the simulation and implementation is given. Finally, the experiment result on-board is shown that our hardware implementation can meet the requirement of real-time signal processing.
Cite This Paper
Lan Yang, Xiang-mo Zhao, Fei Hui,Xin Shi, "An Improved Wavelet Filtering Algorithm and Its FPGA Implementation", International Journal of Information Technology and Computer Science(IJITCS), vol.2, no.2, pp.17-24, 2010. DOI: 10.5815/ijitcs.2010.02.03
Reference
[1] Donoho D I. De-noising by soft-threshold. IEEE Trans. Inform.Theory,1995,41(3):613-627.
[2] Donoho DL，Johnstone I M．Adapting to Unknown Smoothness Via Wavelet Shrinkage[J]．Journal of American Stat Assoc，1995，12(90)：1200-1224.
[3] G. Strang and T. Nguyen, "Wavelets and filter banks," Wellesley- Cambridge Press, 1997.
[4] Engin Avci, Comparison of wavelet families for texture classification by using wavelet packet entropy adaptive network based fuzzy inference system, Applied Soft Computing, v.8n.1,p.225-231,January, 2008 .
[5] Nevin A Elghamery, S.E.-D.Habib. An efficient FPGA implementation of a wavelet coder/decoder. Microelectronics, 2000. ICM 2000. Proceedings of the 12th International Conference on Oct.2000.269-272.
[6] M.Nibouche, A.Bouridane. An FPGA-based wavelet transforms coprocessor. Image processing, 2001. Prceedings.2001 International Conference on Oct.2001.3.194-197.
[7] T.T.Cai,B.W.Silverman.Incorporating information on neighbouring coefficients into wavelet estimation.Sankhya: The Indian Journal of Statistics,63(B),Pt.2,2001:127-148.
[8] Tian Xin, Tan Yihua, Tian Jinwen,New design for 9/7-tap wavelet filter and its VLSI implementation.Jisuanji Xuebao/Chinese Journal of Computers.Vol.31,no.3,pp.411-418.Mar.2008.
[9] M. Nibouche, O. Nibouche, A. Bouridane, "Design and implementation of wavelet based system," Proc. of the 10th IEEE Conf. on Elect., Circuits and Systems, vol. 2, pp. 14-17, 2003.
[10] J. Carletta, G. Giakos N. Patnekar, L. Fraiwan and F. Krach, Design of a field programmable gate array-based platform for real-time denoising of optical imaging signals using wavelet transforms ,Elsevier, vol.36, 2004 289-296.
[11] Peng Jiang, Qingbo Huang, Yaguang Kong1, and Li Chai,Research on a Denoising Method Based on Wavelet Packet Shrinkage for Pulp Thickness Signals.The First International IEEE conference of Multi-Symposiums on Computer and Computational Sciences (IMSCCS'06).2006.
[12] L. Brechet, M. Lucas, C. Doncarli, and D. Farina, "Compression of Biomedical Signals With Mother Wavelet Optimization and Best-Basis Wavelet Packet Selection," IEEE Trans on Biomedical Engineeiring, Vol. 54, NO. 12, p.p. 2186- 2192, Dec 2007.
[13] Donoho DL，Johnstone I M．Ideal Spatial Adaptation Via Wavelet Shrinkage[J]．Biometrika，1994，81(12)：425-455.
[14] “Virtex-5 Family Series Field Programmable Gate Arrays”, Xilinx 2009.