Α Modified EMD-ACWA Denoising Scheme using a Noise-only Model

I Tellala,N Amardjia,A Kesmia

doi:10.48084/etasr.3406

Abstract

This paper describes a modified denoising approach combining Empirical Mode Decomposition (EMD) and Adaptive Center-Weighted Average (ACWA) filter. The Intrinsic Mode Functions (IMFs), resulting from the EMD decomposition of a noisy signal, are filtered by the ACWA filter, according to the noise level estimated in each IMF via a noise-only model. The noise levels of IMFs are estimated by the characteristics of fractional Gaussian noise through EMD. It is found that this model provides a better estimation of noise compared to the absolute median deviation of the signal used in the conventional method. The proposed EMD-ACWA scheme is tested on simulation and real data with different white Gaussian noise levels and the results are compared with those obtained by the conventional EMD-ACWA, EMD Interval Thresholding (EMD-IT) and wavelet methods. Test results show that the proposed approach has a superior performance over the other methods considered for comparison.

Highlights

Signal denoising is a key process in speech, image, and other signal processing applications
An improved Empirical Mode Decomposition (EMD)-Adaptive Center-Weighted Average (ACWA) denoising scheme is proposed by estimating the noise energies of all Intrinsic Mode Functions (IMFs) using an energy model, called noise-only model, introduced in [24] and which gives a better estimate of the noise contained in each IMF
When applied to the simulated signals, the proposed approach leads to gains between 1 to 4dB compared to the conventional EMD-ACWA method, 0.55 to 1.84dB compared to EMD interval thresholding (EMD-IT) one and 1.45 to 7.2dB compared to the wavelet one

Summary

INTRODUCTION

Signal denoising is a key process in speech, image, and other signal processing applications. In [18], a denoising approach, called EMD interval thresholding (EMD-IT), was developed by applying the wavelet thresholding principle to the IMFs resulting from the EMD decomposition. Authors in [1, 19] proposed a novel EMD-based denoising method by applying the adaptive center weighted average (ACWA) filter to the IMFs and provided the term EMD-ACWA. The ACWA is a simple filter which has been used largely in white noise suppression in image enhancement applications [20, 21]. A modified EMD-ACWA method for signal denoising is proposed by adding an improvement to the strategy developed in [1]. The proposed EMD-ACWA denoising scheme is tested on real speech signals of CORPORA database [22], real ECG records from the MIT-BIH Arrhythmia database [23], and different simulation signals

EMPIRICAL MODE DECOMPOSITION

Conventional EMD-ACWA Approach

Proposed EMD-ACWA Denoising

RESULTS AND DISCUSSION

CONCLUSION