• Proceedings of the Korean Society of Radiological Science
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• 2004.09a
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• pp.76.2-76.2
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• 2004

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.2
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• pp.70-76
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• 2009

This paper introduces an evaluation code, which can numerically express the noise possessing degree of signals. By using this code, the best kind and setting of noise suppressing techniques can be chosen automatically. This code is applied to three kinds of specific denoising techniques; those are simple noise removing method in the count versus phase distribution, fuzzy logic method based on noise type in magnitude versus phase plot, and lastly, the technique using grouping characteristics of PD pulses in 3D plot of magnitude versus phase versus cycle. The algorithm shows good performance in the various real PD signals measured from various high voltage apparatuses in Korea.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.9
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• pp.1689-1696
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• 2017

In the process of obtaining and transmitting image, there is degradation of image due to various noise, and there have been many active studies ongoing to remove the noise added on the images. This thesis has proposed a switching filter processing by the types of noise in order to remove the complex noise added on images. When the center value of local mask is damaged by AWGN based on the noise judgment, the threshold value is applied on standard deviation of local mask to process by applying different weight of weighted mask, and if the image is damaged by the salt and pepper noise, the local mask is subdivided into 4 directions, and processed by applying cubic spine interpolation in the direction with the least slat and pepper noise. Also, in order to evaluate the performance of proposed filter algorithm, the study conducted comparison among the existing methods and proposed filter using PSNR.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.2 s.308
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• pp.63-71
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• 2006

Denoising and reconstruction of color images are extensively studied in the field of computer vision and image processing. Especially, denoising and reconstruction of color face images are more difficult than those of natural images because of the structural characteristics of human faces as well as the subtleties of color interactions. In this paper, we propose a denoising method based on PCA reconstruction for removing complex color noise on human faces, which is not easy to remove by using vectorial color filters. The proposed method is composed of the following five steps: training of canonical eigenface space using PCA, automatic extraction of facial features using active appearance model, relishing of reconstructed color image using bilateral filter, extraction of noise regions using the variance of training data, and reconstruction using partial information of input images (except the noise regions) and blending of the reconstructed image with the original image. Experimental results show that the proposed denoising method maintains the structural characteristics of input faces, while efficiently removing complex color noise.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.255-257
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• 2018

Recently, as the frequency of use of video media increases in various fields, the importance of signal processing is increasing. However, many kinds of noise are generated in the transmission and reception process and affect the information of the signal. For this reason, the noise removal is essential as a preprocessing process. In this paper, we propose an algorithm to remove mixed noise of impulse noise and AWGN. The proposed algorithm restores the image through noise determination and pixel change for efficient noise removal. Unlike the conventional method, noise is removed by minimizing both noise effects. Simulation showed excellent noise removal characteristic results were compared and analyzed using the PSNR for such decisions.

• The Journal of the Acoustical Society of Korea
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• v.16 no.5
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• pp.96-104
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• 1997

In this paper, we proposed new methods for estimation of time delay and time-frequency delay in impulsive noise environment. The proposed methods are developed using the theory of ${\alpha}-stable$ distribution, including the fractional negative order moment(FNOM) and minimum dispersion(MD), which are formulated for the time delay estimation and the fractional negative order ambiguity function and complex minimum dispersion, which are difined for the joint estimation of time delay and frequency delay. Through simulation work, its performance was compared with various other algorithms. As a result, while the conventional approaches based on second-order statistics are only verified in Gaussian noise environent ($S{\alpha}S$ noise with ${\alpha}$=2) and also the recently proposed robust methods by Nikias[7] are verified only in limited impulse noise ($S{\alpha}S$ noise with the range of $1<{\alpha}{\le}2$), the methods proposed are able to estimate the time delay in Gaussian and any impulsive noise environments($S{\alpha}S$ noise with the range of $0<{\alpha}{\le}2$).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.5
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• pp.1064-1070
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• 2012

Nowadays, image processing has been applied in a variety of fields. In order to preserve the high quality of visual the degradation phenomenon for images should be removed. Noise is one of the representative elements cause of the degradation phenomenon and AWGN(additive white Gaussian noise) always damages images. In this paper, an mixed filter algorithm, which is based on parallel denoising method, is proposed to suppress AWGN. This algorithm parallels the spatial domain wiener filter and the wavelet domain thresholding method which thresholding function is selected based on scale level. The proposed modified thresholding function which considers the dependency between parent and child coefficient performs well on suppressing noise.

• Journal of Digital Convergence
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• v.10 no.10
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• pp.277-282
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• 2012

The speech recognition system can not quickly adapt to varied environmental noise factors that degrade the performance of recognition. In this paper, the echo noise robust HMM learning model using average estimator LMS algorithm is proposed. To be able to adapt to the changing echo noise HMM learning model consists of the recognition performance is evaluated. As a results, SNR of speech obtained by removing Changing environment noise is improved as average 3.1dB, recognition rate improved as 3.9%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.8B
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• pp.1183-1188
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• 2001

잡음 재밍과 톤 재밍의 혼합 재밍이 존재하는 Rayleigh 페이딩 환경에서 재머상태정보(JSI)를 이용한 FH/MFSK 시스템의 성능 향상을 분석하였다. 송신 신호와 재머 성분은 각각 Rayleigh 페이딩 환경의 영향을 받으며, 재머상태 정보는 잡음 잡음의 전력이나 톤 재밍의 크기 및 전력을 알 수 있다고 가정하였다. 분석 결과, JSI를 이용한 시스템이 잡음성 재밍의 비율 변동에 관계없이 JSI를 고려하지 않는 시스템보다 성능 향상을 얻을 수 있다. $E_{s}$ /$J_{o}$ =10[dB]인 Rayleigh 페이딩환경에서 JSI가 없는 시스템의 경우, 잡음재밍이 비율에 관계없이 최대의 성능 열화값을 갖는 톤 재밍의 비율은 0.1이나, JSI를 이용한 시스템은 다른 값을 가지게 되어, 잡음성 재밍과 톤 재밍의 적절한 비율이 시스템의 성능저하에 최대로 영향을 끼칠 수 있음을 알 수 있다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.12
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• pp.2798-2804
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• 2010

The audio and image signal are corrupted by various noises in signal processing, many studies are being accomplished to restore those signals. In this paper, the algorithm is proposed to remove additive Gaussian noise and impulse noise at one dimension signal like an speech signal. The algorithm is composed to remove Gaussian noise after removing impulse noise. And the method using wavelet coefficient accumulation is used to remove the Gaussian noise, and the median filter based on element deviation is applied to remove the impulse noise. Also we compare existing methods using SNR(signal-to-noise ratio) as the standard of judgement of improvemental effect.