Practical Methods for Noise Removal: Applications to Spikes, Nonstationary Quasi-Periodic Noise, and Baseline Drift

2009 ◽  
Vol 81 (12) ◽  
pp. 4987-4994 ◽  
Author(s):  
Delphine Feuerstein ◽  
Kim H. Parker ◽  
Martyn G. Boutelle
Keyword(s):  
Noise Removal ◽  
Baseline Drift ◽  
Periodic Noise

scholarly journals Periodic Noise Removal in Strain and Natural Images Using 2-D Fast Fourier Transform

2013 ◽  
pp. 90-94
Author(s):  
Mandeep Kaur ◽  
Dinesh Kumar ◽  
Ekta Walia ◽  
Manjit Sandhu
Keyword(s):  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Frequency Domain ◽  
Noise Removal ◽  
Natural Images ◽  
Periodic Pattern ◽  
Periodic Noise ◽  
Mean Filter ◽  
The Mean

This paper presents a 2-D FFT removal algorithm for reducing the periodic noise in natural and strain images. For the periodic pattern of the artifacts, we apply the 2-D FFT on the strain and natural images to extract and remove the peaks which are corresponding to periodic noise in the frequency domain. Further the mean filter applied to get more effective results. The performance of the proposed method is tested on both natural and strain images. The results of proposed method is compared with the mean filter based periodic noise removal and found that the proposed method significantly improved for the noise removal.

A Non-Linear Approach to ECG Signal Processing using Morphological Filters

2013 ◽  
Vol 3 (3) ◽  
pp. 46-59 ◽  
Author(s):  
Vikrant Bhateja ◽  
Rishendra Verma ◽  
Rini Mehrotra ◽  
Shabana Urooj
Keyword(s):  
Signal Processing ◽  
Noise Removal ◽  
High Signal ◽  
Ecg Signal ◽  
Processing Scheme ◽  
Baseline Drift ◽  
Ecg Signals ◽  
Non Linear ◽  
Ecg Signal Processing ◽  
Electrocardiogram Ecg

Analysis of the Electrocardiogram (ECG) signals is the pre-requisite for the clinical diagnosis of cardiovascular diseases. ECG signal is degraded by artifacts such as baseline drift and noises which appear during the acquisition phase. The effect of impulse and Gaussian noises is randomly distributed whereas baseline drift generally affects the baseline of the ECG signal; these artifacts induce interference in the diagnosis of cardio diseases. The influence of these artifacts on the ECG signals needs to be removed by suitable ECG signal processing scheme. This paper proposes combination of non linear morphological operators for the noise and baseline drift removal. Non flat structuring elements of varying dimensions are employed with morphological filtering to achieve low distortion as well as good noise removal. Simulation outcomes illustrate noteworthy improvement in baseline drift yielding lower values of MSE and PRD; on the other hand high signal to noise ratios depicts suppression of impulse and Gaussian noises.

Periodic noise removal using local thresholding

2016 ◽  
Author(s):  
Vipin Prakash Yadav ◽  
Gajendra Singh ◽  
Md. Imtiyaz Anwar ◽  
Arun Khosla
Keyword(s):  
Noise Removal ◽  
Periodic Noise ◽  
Local Thresholding

A windowed Gaussian notch filter for quasi-periodic noise removal

2008 ◽  
Vol 26 (10) ◽  
pp. 1347-1353 ◽  
Author(s):  
Igor Aizenberg ◽  
Constantine Butakoff
Keyword(s):  
Notch Filter ◽  
Noise Removal ◽  
Periodic Noise
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