New Denoising Method Based on Empirical Mode Decomposition and Improved Thresholding Function

2016 International Conference on Communication, Image and Signal Processing

物理学;无线电电子学;计算机科学

Mohguen, Wahiba^1 ; Hadibekka, Raïsel^1

Université de Sétif 1, Faculty of Technology, Department of Electronics, LIS Laboratory, Sétif

19000, Algeria^1

关键词: Denoising methods;    Empirical Mode Decomposition;    Intrinsic Mode functions;    Mean Square Error (MSE);    Noisy signals;    Soft thresholding;    Thresholding;    Traditional approaches;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/787/1/012014/pdf
DOI  :  10.1088/1742-6596/787/1/012014

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

This paper presents a new denoising method called EMD-ITF that was based on Empirical Mode Decomposition (EMD) and the Improved Thresholding Function (ITF) algorithms. EMD was applied to decompose adaptively a noisy signal into intrinsic mode functions (IMFs). Then, all the noisy IMFs were thresholded by applying the improved thresholding function to suppress noise and improve the signal to noise ratio (SNR). The method was tested on simulated and real data and the results were compared to the EMD-Based signal denoising methods using the soft thresholding. The results showed the superior performance of the new EMD-ITF denoising over the traditional approach. The performance were evaluated in terms of SNR in dB, and Mean Square Error (MSE).