Title :
Noise suppression by removing singularities
Author :
Shekarforoush, H.
Author_Institution :
Center for Autom. Res., Maryland Univ., College Park, MD, USA
fDate :
7/1/2000 12:00:00 AM
Abstract :
A method is proposed for suppressing Gaussian noise by extracting local singularities. The method is based on truncating Riemann series decomposition, whose components naturally characterize different orders of Holder regularity. The approach yields a single-step filtering technique whose performance is comparable to three-step wavelet decomposition and thresholding techniques
Keywords :
Gaussian noise; filtering theory; interference suppression; Gaussian noise suppression; Holder regularity; Riemann series decomposition; local singularities extraction; single-step filtering technique; three-step wavelet decomposition; thresholding techniques; Covariance matrix; Filtering; Gaussian noise; Interference; Maximum likelihood detection; Noise robustness; Random processes; Signal processing algorithms; Testing; Training data;
Journal_Title :
Signal Processing, IEEE Transactions on
