Abstract

This communication aims to combine several previously proposed wavelet denoising algorithms into a novel heuristic block method. The proposed ``hysteresis'' thresholding uses two thresholds simultaneously in order to combine detection and minimal alteration of informative features of the processed signal. This approach exploits the graph structure of the wavelet decomposition to detect clusters of significant wavelet coefficients. The new algorithm is compared with classical denoising methods on simulated benchmark signals.

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