Wavelet denoising of ultrasonic A-scans by random partial cycle spinning

Emeterio, José Luis San; Rodríguez-Hernández, Miguel A.

doi:10.1109/ultsym.2012.0113

Cited by 10 publications

(16 citation statements)

References 19 publications

(25 reference statements)

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“…In the previous research about developing a conversion curve from an echo signal [12][13][14][15], the method to remove the noise of the signal is not discussed in detail, it is either because the echo signal can instantly be processed or because the need for signal pre-processing is not necessary. However, in some cases [14][15][16], a pre-processing is required for the echo signal in order to obtain the best quality of the signal parameters applied for developing a conversion curve.…”

Section: Related Workmentioning

confidence: 99%

“…The Wavelet transform can also be applied to detect the peak of the signal more precisely, compared to the conventional peak detection such as curve fitting method. There are previously some researches which applied the Wavelet method in Ultrasonic field [14][15][16]. An analysis in time-frequency domain is also performed with the Scalogram as the output, to observe the parameters of the signal such as time, frequency, and the amplitude as the signal propagates through the medium.…”

Section: Introductionmentioning

confidence: 99%

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The Enhancement of 3 MHz Ultrasonic Echo Signal for Conversion Curve Development for Acoustic Impedance Estimation by Using Wavelet Transform

Prastika

Gunawan

Dewantara

et al. 2018

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Ultrasonic technology has already been applied for many applications. Most of them are mainly used for object measurement. Some techniques have been widely applied to particular measurement by utilizing a very specific component. In this research, the previous technique to develop a conversion curve to obtain the acoustic impedance of the target is adopted. Then, a 3 MHz concave shaped ultrasonic transducer for measuring liquids is proposed and a confirmation is needed to confirm if the system is correct. Therefore, several saline solutions with some known properties are used. A low voltage of 10 Volt pulse is sent to trigger the transducer. The ultrasonic wave is transmitted through the multilayered mediums, which is pure water, clear acrylic, and the target. The echo from the interface between the acrylic and the target is then received by the same transducer. Some parameters such as peak and Root Mean Square (RMS) are used to develop the conversion curve. A peak detection and comparison between the original echo and the processed one by using Wavelet transform is performed. Some analysis of the echo signal by using multiresolution and timefrequency analysis are also proposed. The result obtained from the measurement is then compared to the theoretical calculation. Based on the result, in terms of developing the conversion curve, only the RMS value of the Undecimated Wavelet Transform (UWT) which has the closest trend to the result of the calculation, with the mean percentage error of 0.65512%, which is the smallest value among all parameters.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Enhancement of 3 MHz Ultrasonic Echo Signal for Conversion Curve Development for Acoustic Impedance Estimation by Using Wavelet Transform

Prastika

Gunawan

Dewantara

et al. 2018

emitter

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“…Experimental noise registers were acquired from areas without artificial defects and an ultrasonic pulse-echo response of the transducer was obtained using the back wall echo from a methacrylate block [26]. Registers were obtained with 2500 data samples.…”

Section: Rpcs Denoising Of Ultrasonic A-scans Composed From Experimenmentioning

confidence: 99%

“…Wavelet denoising using either DWT or SWT is a well established and efficient method for ultrasonic signal denoising. In particular, wavelet techniques have been used for noise reduction and flaw detection in different NDE ultrasonic applications [12][13][14][15][16][17][18][19][20][21][22][23][24][25][26]. It is considered as a non-parametric method, since any particular model is assumed and therefore any parameter must be estimated.…”

Section: Introductionmentioning

confidence: 99%

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Wavelet Cycle Spinning Denoising of NDE Ultrasonic Signals Using a Random Selection of Shifts

Emeterio

Rodríguez-Hernández

2014

J Nondestruct Eval

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Wavelets are a powerful tool for signal and image denoising. Most of the denoising applications in different fields were based on the thresholding of the discrete wavelet transform (DWT) coefficients. Nevertheless, DWT transform is not a time or shift invariant transform and results depend on the selected shift. Improvements on the denoising performance can be obtained using the stationary wavelet transform (SWT) (also called shift-invariant or undecimated wavelet transform). Denoising using SWT has previously shown a robust and usually better performance than denoising using DWT but with a higher computational cost. In this paper, wavelet shrinkage schemes are applied for reducing noise in synthetic and experimental non-destructive evaluation (NDE) ultrasonic A-scans, using DWT and a cycle-spinning implementation of SWT.A new denoising procedure, which we call Random Partial Cycle Spinning (RPCS), is presented. It is based on a cycle-spinning over a limited number of shifts that are selected in a random way. Wavelet denoising based on DWT, SWT and RPCS have been applied to the same sets of ultrasonic A-scans and their performances in terms of SNR are compared. In all cases three well known threshold selection rules (Universal, Minimax and Sure), with decomposition level dependent selection, have been used. It is shown that the new procedure provides a good robust denoising performance, without the DWT fluctuating performance, and close to SWT but with a much lower computational cost.

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Shift selection influence in partial cycle spinning denoising of biomedical signals

Rodríguez-Hernández

2016

Biomedical Signal Processing and Control

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Denoising of biomedical signals using wavelet transform is a widely used technique. The use of undecimated wavelet transform (UWT) assures better denoising results but implies a higher complexity than discrete wavelet transform (DWT). Some implementation schemes have been proposed to perform UWT, one of them is Cycle Spinning (CS). CS is performed using the DWT of several circular shifted versions of the signal to analyse. The reduction of the number of shifted versions of the biomedical signal during denoising process used is addressed in the present work. This paper is about a variant of CS with a reduced number of shifts, called Partial Cycle Spinning (PCS), applied to ultrasonic trace denoising. The influence of the choice of PCS shifts in the denoised registers quality is studied. Several shifts selection rules are proposed, compared and evaluated. Denoising results over a set of ultrasonic registers are provided for PCS with different shift selection rules, CS and DWT. The work shows that PCS with the appropriate choice of shifts could be the best option to denoise biomedical ultrasonic traces.

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Wavelet denoising of ultrasonic A-scans by random partial cycle spinning

Cited by 10 publications

References 19 publications

The Enhancement of 3 MHz Ultrasonic Echo Signal for Conversion Curve Development for Acoustic Impedance Estimation by Using Wavelet Transform

The Enhancement of 3 MHz Ultrasonic Echo Signal for Conversion Curve Development for Acoustic Impedance Estimation by Using Wavelet Transform

Wavelet Cycle Spinning Denoising of NDE Ultrasonic Signals Using a Random Selection of Shifts

Shift selection influence in partial cycle spinning denoising of biomedical signals

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