• Journal of Magnetics
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• v.22 no.1
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• pp.55-59
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• 2017

The purpose of this study was to quantitatively evaluate image quality using intensity profile, coefficient of variation (COV), and peak signal to noise ratio (PSNR) with respect to noise reduction techniques in the ultrasound images. For that purpose, we compared with the median filter, Rudin-Osher-Fatemi (ROF), Anscombe and proposed patch group prior based denoising (PGPD) techniques. To evaluate image quality, the Shepp-Logan phantom and the ultrasound image were acquired using simulation and experiment, respectively. According to the results, the difference of intensity profile using PGPD technique is lowest compared with original Shepp-Logan phantom. In simulation, the measured COV was 0.249, 0.198, 0.198, 0.177, and 0.080 using noisy, median, ROF, Anscombe and PGPD technique, respectively. Also, in experimental image, the measured COV was 0.245, 0.230, 0.231, 0.242 and 0.187 using noisy, median, ROF, Anscombe and PGPD technique, respectively. Especially, when we used PGPD technique, the PSNR has highest value in both simulation and experiment. In this study, we performed simulation and experiment study to compare various denoising techniques in the ultrasound image. We can expect the PGPD technique to improve in medical diagnosis with excellent noise reduction.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.86-91
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• 2002

The regression analysis in the six sigma process is used to reduce the vibration of an electric grinder. The vibration characteristics and the contribution of each part to overall vibration of the electric grinder is investigated through various vibration measurements and frequency analysis for the assembled and disassembled one. Then the application of the regression analysis finds out that the rotating components of the armature have more severe contributions to the overall vibration than the frequency components of the fan or the gear part, which is decided with higher value of the coefficient of determination. The unbalance and looseness of the armature and the fan are tested again by the regression analysis in order to decide how much unbalance or looseness should be reduced for the predetermined goal of vibration level of the electric grinder. These results show that the regression analysis can be a valuable tool in production line to decide where and how much faults needs to be adjusted for the reduction of vibration and noise.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.1071-1076
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• 2002

The purpose of this paper is to examine sound absorption characteristics of sintered Al(aluminum) plate. Comparison between experiment and theoretical analysts by using empirical formula are made. Based on comparison. it is found that Voronina model gives more reasonable explanation for sound absorption characteristics of sintered Al plates. Effect of air gap with varying the thickness of plates are also investigated, which concludes that the air gap generally increase absorption but for too thick thickness of Al plates. Al plates with air gap shows 0.85∼0.9 of NRC(Noise Reduction Coefficient) measured in reverberation room. which is comparable to glass wool. Comparison between normal and random Incident absorption shows that random incident absorption is higher than normal incident absorption.

• Journal of Broadcast Engineering
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• v.13 no.5
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• pp.565-573
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• 2008

This paper proposes noise reduction methods to improve the channel estimation performance in Equalization On-Channel Repeater (E-OCR) for Terrestrial-Digital Multimedia Broadcasting (T-DMB) system. In the E-OCR for T-DMB system, the channel estimation is performed by the pilot signal extraction and the channel coefficient estimation. Since the performance of the channel estimation highly depends on the estimated channel coefficients whose accuracy is associated with the received signal-to-noise ratio (SNR), it is important to reduce noise existing at the estimated channel coefficients. To reduce such noise components, various noise reduction methods of the estimated channel coefficients based on the M -point weighted moving average are proposed. Computer simulations show that the proposed methods improve the estimation performance by more than 2 to 3 dB in terms of the symbol error rate after equalization.

• Journal of Sensor Science and Technology
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• v.21 no.2
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• pp.144-150
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• 2012

A microphone for fully implantable hearing device was generally implanted under the skin of the temporal bone. So, the implanted microphone's characteristics can be affected by the accompanying noise due to masticatory movement. In this paper, the implantable microphone with 2-channels structure was designed for reduction of the generated noise signal by masticatory movement. And an experimental model for generation of the noise by masticatory movement was developed with considering the characteristics of human temporal bone and skin. Using the model, the speech signal by a speaker and the artificial noise by a vibrator were supplied simultaneously into the experimental model, the electrical signals were measured at the proposed microphone. The collected signals were processed using a general adaptive filter with least mean square(LMS) algorithm. To confirm performance of the proposed methods, the correlation coefficient and the signal to noise ratio(SNR) before and after the signal processing were calculated. Finally, the results were compared each other.

• Proceedings of the Korea Contents Association Conference
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• 2003.05a
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• pp.376-382
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• 2003

Recently, there have been many types of wavelet transformations proposed to remove the noise from an signal and image data By using feature of seperating the noise from the original image the Wavelet transformations can retain the edges of the images The wavelet analysis is complete when the basis function is coded into the wavelet This Thesis describes a method of using wavelet transformation to remove the noise from an image signal. Although the wavelet transformation proposed by Donoho and Johnstone works, it does not reliably remove all the noise from the images. So this thesis propose an algorithm that selected Wavelet Shrinkgae and threshold according to the features of bands and amplitude of noise.

• Nuclear Engineering and Technology
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• v.52 no.10
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• pp.2328-2333
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• 2020

The filter technique was applied to noise images, as noise is the significant factor that cause poor image quality due to lower photon counting. The purpose of this study is to confirm that image quality can be improved using the median modified Wiener filter (MMWF) technique; this is achieved via a National Electrical Manufacturers Association International Electrotechnical Commission body phantom with four large spheres that are filled with the ^99mTc radioisotope when evaluating the image quality. Conventional filters such as Wiener, Gaussian, and median filters were designed, and signal to noise ratio, coefficient of variation, and contrast to noise ratio were used as the evaluation parameters. The improvement in the image quality was in the following order, from the least to the highest improvement, in all cases: Wiener filter, Gaussian filter, median filter, and the MMWF technique. The results show that the image quality was improved from 20.6 to 65.5%, 7.4-40.3%, and 12.7-44.7% for the SNR, COV, and CNR values, respectively, when using the MMWF technique, compared with the use of conventional filters. In conclusion, our results demonstrated that the MMWF technique is useful for reducing the noise distribution in gamma camera images.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.695-706
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• 2014

Partial discharge (PD) measurements have emerged as a dominant investigative tool for condition monitoring of insulation in high voltage equipment. But the major problem behind them the PD signal is severely polluted by several noises like White noise, Random noise, Discrete Spectral Interferences (DSI) and the challenge lies with removing these noise from the onsite PD data effectively which leads to preserving the signal for feature extraction. Accordingly the paper is mainly classified into two parts. In first part the PD signal is artificially simulated and mixed with white noise. In second part the PD is measured then it is subjected to the proposed denoising techniques namely Translation Invariant Wavelet Transform (TIWT). The proposed TIWT method remains the edge of the original signal efficiently. Additionally TIWT based denoising is used to suppress Pseudo Gibbs phenomenon. In this paper an attempt has been made to review the methodology of denoising the PD signals and shows that the proposed denoising method results are better when compared to other wavelet-based approaches like Fast Fourier Transform (FFT), Discrete Wavelet Transform (DWT), by evaluating five different parameters like, Signal to noise ratio, Cross-correlation coefficient, Pulse amplitude distortion, Mean square error, Reduction in noise level.

• Korean Journal of Optics and Photonics
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• v.11 no.2
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• pp.97-101
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• 2000

We proposed and demonstrated a new scheme for subtracting the source excess noise from the output of the fiber-optic gyroscope. Unlike the previous methods, this scheme has an advantage of not requiring a delaying fiber for source noise detection and can be simply applied to fiber gyroscope operating at the proper frequency. By usmg this scheme. the proper frequency component of the source excess noise was subtracted from the gyroscope output. As a result, we obtained the reduction of noise by 12 dB (electrical) which was measured from the noise floor spectrum in the fiber gyroscope modulated at the proper frequency. We also obtarned !be random walk coefficient of thc gyro output reduced by a factor of 3.5. f 3.5.

• Journal of the Korean Society of Radiology
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• v.13 no.5
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• pp.765-771
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• 2019

Noise in skull X-ray imaging is inevitable, which reduces imaging quality and diagnostic accuracy and increases errors due to the nature of digital imaging devices. Increasing the dose can attenuate noise, but that could lead to big problems with higher exposure dose received by patients. Thus, noise reduction algorithms are actively being studied at low doses to solve dose problems and reduce noise at the same time. Wiener filter and median filter have been widely used, with the disadvantages of poor noise reduction efficiency and loss of much information about imaging boundary. The purpose of this study is to apply total variation (TV) algorithm to skull X-ray imaging that can compensate for the problems of previous noise reduction efficiency to assess quantitatively and compare them. For this study, skull X-ray imaging is obtained using various kVp and mAs using the skull phantom using the X-ray device of Siemens. In addition, contrast to noise ratio (CNR) and coefficient of variation (COV) are compared and measured when noisy image, median filter, Wiener filter and TV algorithm were applied to each phantom imaging. Experiments showed that when TV algorithms were applied, CNR and COV characteristics were excellent under all conditions. In conclusion, we've been able to see if we can use TV algorithm to improve image quality and CNR could be seen to increase due to the decrease in noise as the amount of increased mAs. On the other hand, COV decreased as the amount of increased mAs, and when kVp increased, noise was reduced and the transmittance was increased, so COV was reduced.