IEICE TRANSACTIONS on Fundamentals
Enhancement of Fractal Signal Using Constrained Minimization in Wavelet Domain
Summary :
In recent years, fractal processes have played important roles in various application fields. Since a 1/f process possesses the statistical self-similarity, it is considered sa a main part of fractal signal modeling. On the other hand, noise reduction is often needed in real-world signal processing. Hence, we propose an enhancement algorithm for 1/f signal disturbed by white noise. The algorithm is based on constrained minimization in a wavelet domain: the power of 1/f signal distortion in the wavelet domain is minimized under a constraint that the power of residual noise in the wavelet domain is smaller than a threshold level. We solve this constrained minimization problem using a Lagrangian equation. We also consider a setting method of the Lagrange multiplier in the proposed algorithm. In addition, we will confirm that the proposed algorithm with this Lagrange multiplier setting method obtains better enhancement results than the conventional algorithm through computer simulations.
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- IEICE TRANSACTIONS on Fundamentals Vol.E80-A No.6 pp.958-964
- Publication Date
- 1997/06/25
- Publicized
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- Special Section PAPER (Special Section on Signal Processing Theories and Applications Based on Modelling of Nonstationary Processes)
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Jun'ya SHIMIZU, Yoshikazu MIYANAGA, Koji TOCHINAI, "Enhancement of Fractal Signal Using Constrained Minimization in Wavelet Domain" in IEICE TRANSACTIONS on Fundamentals,
vol. E80-A, no. 6, pp. 958-964, June 1997, doi: .
Abstract: In recent years, fractal processes have played important roles in various application fields. Since a 1/f process possesses the statistical self-similarity, it is considered sa a main part of fractal signal modeling. On the other hand, noise reduction is often needed in real-world signal processing. Hence, we propose an enhancement algorithm for 1/f signal disturbed by white noise. The algorithm is based on constrained minimization in a wavelet domain: the power of 1/f signal distortion in the wavelet domain is minimized under a constraint that the power of residual noise in the wavelet domain is smaller than a threshold level. We solve this constrained minimization problem using a Lagrangian equation. We also consider a setting method of the Lagrange multiplier in the proposed algorithm. In addition, we will confirm that the proposed algorithm with this Lagrange multiplier setting method obtains better enhancement results than the conventional algorithm through computer simulations.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e80-a_6_958/_p
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@ARTICLE{e80-a_6_958,
author={Jun'ya SHIMIZU, Yoshikazu MIYANAGA, Koji TOCHINAI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Enhancement of Fractal Signal Using Constrained Minimization in Wavelet Domain},
year={1997},
volume={E80-A},
number={6},
pages={958-964},
abstract={In recent years, fractal processes have played important roles in various application fields. Since a 1/f process possesses the statistical self-similarity, it is considered sa a main part of fractal signal modeling. On the other hand, noise reduction is often needed in real-world signal processing. Hence, we propose an enhancement algorithm for 1/f signal disturbed by white noise. The algorithm is based on constrained minimization in a wavelet domain: the power of 1/f signal distortion in the wavelet domain is minimized under a constraint that the power of residual noise in the wavelet domain is smaller than a threshold level. We solve this constrained minimization problem using a Lagrangian equation. We also consider a setting method of the Lagrange multiplier in the proposed algorithm. In addition, we will confirm that the proposed algorithm with this Lagrange multiplier setting method obtains better enhancement results than the conventional algorithm through computer simulations.},
keywords={},
doi={},
ISSN={},
month={June},}
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TY - JOUR
TI - Enhancement of Fractal Signal Using Constrained Minimization in Wavelet Domain
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 958
EP - 964
AU - Jun'ya SHIMIZU
AU - Yoshikazu MIYANAGA
AU - Koji TOCHINAI
PY - 1997
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E80-A
IS - 6
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - June 1997
AB - In recent years, fractal processes have played important roles in various application fields. Since a 1/f process possesses the statistical self-similarity, it is considered sa a main part of fractal signal modeling. On the other hand, noise reduction is often needed in real-world signal processing. Hence, we propose an enhancement algorithm for 1/f signal disturbed by white noise. The algorithm is based on constrained minimization in a wavelet domain: the power of 1/f signal distortion in the wavelet domain is minimized under a constraint that the power of residual noise in the wavelet domain is smaller than a threshold level. We solve this constrained minimization problem using a Lagrangian equation. We also consider a setting method of the Lagrange multiplier in the proposed algorithm. In addition, we will confirm that the proposed algorithm with this Lagrange multiplier setting method obtains better enhancement results than the conventional algorithm through computer simulations.
ER -
English
