Browse > Article

A Noise De-Noising Technique using Binary-Tree Non-Uniform Filter Banks and Its Realization  

Sohn, Sang-Wook (The Department of Electrical Engineering, Chungbuk National University)
Choi, Hun (Korea Research Institute of Standards and Science)
Bae, Hyeon-Deok (The Department of Electrical Engineering, Chungbuk National University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.44, no.5, 2007 , pp. 94-102 More about this Journal
Abstract
In de-noising, it is wellknown that wavelet-thresholding algorithm shows near-optimal performances in the minimax sense. However, the wavelet-thresholding algorithm is difficult in realization it on hardware, such as FPGA, because of wavelet function complexity. In this paper, we present a new do-noising technique with the binary tree structured filter bank, which is based on the signal power ratio of each subbands to the total signal power. And we realize it on FPGA. For simple realization, the filter banks are designed by Hadamard transform coefficients. The simulation and hardware experimental results show that the performance of the proposed method is similar with that of soft thresholding de-noising algorithm based on wavelets, nevertheless it is simple.
Keywords
de-noising; filter banks; FPGA; subband;
Citations & Related Records
연도 인용수 순위
  • Reference
1 S. Haykin, Adaptive Filter Theory, Prentice-Hall, 2002
2 A. H. Sayed, Fundamentals of Adaptive Filtering, Wiley Interscience, 2003
3 S. J. Elliott and P. A. Nelson, 'Active noise control,' IEEE Signal Proc. Magazine, vol. 10, pp. 12-35, Oct. 1993   DOI   ScienceOn
4 P. P. Vaidyanathan, Multirate systems and filter banks, Prentice Hall. Inc, 1993
5 S. Sardy, 'Minimax threshold for denoisincomplex signals with Waveshrink,' IEEE Trans. Signal Processing, vol. 48, Issue 4, pp.1023-1028, Apr. 2000   DOI   ScienceOn
6 S. Mallat, Wavelet tour of signal processing, Academic Press, 1999
7 T. Tanaka and L. Duval, 'Noise cancelling of image with multiple subband transforms,' Proc. ICIP'04, vol. 2, pp. 1209-1212, Oct. 2004
8 R. M. Rao, Wavelet Transforms, Addison Wesley, 1998
9 Altera, Stratix Device Handbook ver. 3.3, Jul. 2005
10 G. Strang, Wavelets and Filter Banks, Wellesley-Cambridge Press, 1997
11 S. L. Walker, S. Y. Foo, and J. Petrone, 'On the performance of a hardware implementation of the wavelet transform,' IEEE Proc. 35th Southeastern Symposium, pp. 397-399, Mar. 2003
12 Z. Zhan and J. Hu, 'FPGA implementation of 4 samples DWT based on the model of pyramidal structural data coding,' IEEE Proc. 4th Computer and Information Technology International Conference, pp. 819-823, Sep. 2004
13 J. B. Weaver, X. Yansun, D. M. Jr. Healy, and L. D. Cromwell, 'Filtering noise from images with wavelet transforms,' Magnetic Resonance in Medicine, vol. 24, pp. 288-295, 1991   DOI
14 Q. Pan, L. Zhang, D. Guanzhong, and Z. Hongai, 'Two denoising method by wavelet transform,' IEEE Trans. Signal Processing, vol. 47, no. 12, pp. 3401-3406, Dec. 1999   DOI   ScienceOn
15 D. L. Donoho, 'Denoising by soft-thresholding,' IEEE Trans. Information Theory, vol. 41, pp. 613-627, May 1995   DOI   ScienceOn
16 W. Shenggian, 'Load characteristic based wavelet shrinkage denoising algorithm.' IEEE electronics Letts., vol. 38, no. 9, pp. 411-412, Apr. 2002   DOI   ScienceOn
17 D. L. Donoho and I. M. Johnstone, 'Threshold selection for wavelet shrinkage of noisy data,' IEEE Proc. New Opportunities for Biomedical Engineers, vol. 1, pp. A24 - A25, Nov. 1994