• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.7 no.1
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• pp.1-14
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• 1996

The purpose of this paper is to analyze the performance of M-ary PSK communication system according to the types of electromagnetic interference in an impulsive noise environment. We have introduced Gaussian, sinusoidal and rectangular waves as a electromagnetic interference. Using the derived equations, we evaluated the error performance of the BPSK and QPSK system in the presence of electromagnetic interference and impulsive noise. From results, we have obtained that the Gaussian wave produced the most significant performance degradation and that sinusoidal wave produced more performance degradation than rectangular wave. Therefore, without knowing the types of electromagnetic interference, it is best to regard it as Gaussian wave when designing a communication system. In addition, we could found out that the error performance degrades as impulsive noise becomes strong and the error performance can not be improved significantly even the electromagnetic interference becomes weak. Therefore, this describes that the impulsive noise affects dominantly to the performance degradation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.10
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• pp.2239-2246
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• 2011

In image signal processing, image signal is corrupted by various noises and caused the degradation phenomenon. And Images often corrupted by AWGN(additive white gaussian noise) and impulse noise which called mixed noise. In this paper, the algorithm is proposed to remove mixed noise while keeping edge information. The proposed algorithm first classifies the noise type, if the classify result is AWGN, then the mean of the output after using self-adaptive weighted mean filter and median value will be the outfiltering value. And if the noise type is impulse noise, then the noise is removed by a modified nonlinear filter. Also we compare existing methods through the simulation and using PSNR(peak signal to noise ratio) as the standard of judgement of improvement effect. The result of computer simulation on test images indicates that the proposed method is superior to traditional filtering algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.8
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• pp.2001-2007
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• 2014

Image signal related technology has been developing via various display equipment development and popularization of contents. However, errors occur in these image contents due to addition of excess noise from several cause during the process of general image signal data processing, transmission and storage. In terms of noise added to the image content, there are various types in accordance with cause of occurrence and form, and it is typically impulse noise, gaussian noise and complex noise which is composed of two types of overlapping noise. In this paper, complex algorithm is suggested in order to lessen the effect of mixed noise added to the image content by putting it through noise judgement process and categorizing each into impulse and gaussian noise and processing them separately. And in order to demonstrate the superiority of the suggested algorithm, PSIN(peak signal to noise ratio) was used as the standard of judgement.

• Journal of the Korean Society of Radiology
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• v.15 no.1
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• pp.21-28
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• 2021

Computed tomography (CT) has the problem of having more radiation exposure compared to other radiographic apparatus. There is a low-dose imaging technique for reducing exposure, but it has a disadvantage of increasing noise in the image. To compensate for this, various noise reduction algorithms have been developed that improve image quality while reducing the exposure dose of patients, of which the median modified Wiener filter (MMWF) algorithm that can be effectively applied to CT devices with excellent time resolution has been presented. The purpose of this study is to optimize the mask size of MMWF algorithm and to see the excellence of noise reduction of MMWF algorithm for existing algorithms. After applying the MMWF algorithm with each mask sizes set from the MASH phantom abdominal images acquired using the MATLAB program, which includes Gaussian noise added, and compared the values of root mean square error (RMSE), peak signal-to-noise ratio (PSNR), coefficient correlation (CC), and universal image quality index (UQI). The results showed that RMSE value was the lowest and PSNR, CC and UQI values were the highest in the 5 x 5 mask size. In addition, comparing Gaussian filter, median filter, Wiener filter, and MMWF with RMSE, PSNR, CC, and UQI by applying the optimized mask size. As a result, the most improved RMSE, PSNR, CC, and UQI values were showed in MMWF algorithms.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2244-2247
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• 2003

In this paper, we present a method which can minimize distortion from desired signal in thoracic sound signal processing. We firstly chose the proper wavelet mother function to reduce noise components. Secondly, we chose a clean thoracic sound, then added Gaussian noise and 3 step(10, 15, 20db) uniform noise to it. Finally, the various wavelet functions are applied for noise cancellation. To evaluate the efficiency of this study, we computed SNR and RSE value. Then we found the optimal mother wavelet function for thoracic sound.

• Journal of IKEEE
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• v.25 no.3
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• pp.544-547
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• 2021

Recently, various display products are being applied to automobiles. In the process of acquiring an image from a display product, a large amount of additive white Gaussian noise(AWGN) is generated. Generally known denoising techniques focus on removing noise, so detailed components including image information are proportionally lost in the process of removing noise. The algorithm proposed in this paper proposes a method to effectively remove noise while preserving the detail of image information.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.43 no.12 s.354
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• pp.8-14
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• 2006

This paper proposed noise insensitive 4*4 mid frequency-OCT (MF-DCT) focus measure operator. Proposed operator enhanced low power 8*8 MDCT operator to have 4*4 rotationally same form for Gaussian noise. MF-DCT operator acting like band-pass filter suppresses both low-frequency signal useless for focus measure and high-frequency signal affected by impulsive noise. Also it is proved to be linear because it uses the energy of band-pass filtered signal as focus measure. Experimental result shows its superiority by comparing AUM with traditional operators.

• Journal of the Korean Institute of Telematics and Electronics
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• v.19 no.3
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• pp.37-45
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• 1982

This paper is a sequel of the Part I paper[1] on the modified digital Costas loop. In this Part II we analyze the performance of the system in the presence of noise. It is shown that, when the input signal is corrupted by additive white Gaussian noise, the noise process in the loop becomes Rician as a result of the tan-1 (.) function of the phase error detector. Steady state probability density functions of phase errors of the first-and second-order loops have been obtained by solving the Chapman-Kolmogorov equation numerically. Also, the mean and variance of phase error in the steady state have been obtained analytically, and are compared with the results obtained by computer simulation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.8
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• pp.1773-1778
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• 2012

Nowadays, the high quality of image is required with the demand for digital image processing devices is rapidly increasing. But image always damaged by many kinds of noises and it is necessary to remove noise and the denoising becomes one of the most important fields. In many cases image is corrupted by AWGN(additive white Gaussian noise). In this paper, we proposed an improved denoising algorithm with edge preservation. The proposed algorithm averages values processed by spatial weighted filter and self adaptive weighted filter. Then we add the value which is computed by the equation considering variance of mask and the estimated noise variance. Through the experience, the proposed filter performs well on noise suppression and edge preservation properties and improves the image visual quality.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.936-939
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• 2015

Recently, the image processing is utilized in various fields and many studies on the image restoration have been carried out in order to remove the noise occurring in the process of data transmission, processing and storage. There are many types of noises added to the image according to the cause and shape, and AWGN(additive white Gaussian noise) is one of typical noises. This paper proposed an algorithm which applies the weighting of filter differently according to the standard deviation in order to alleviate AWGN added to the image, and compared this algorithm with the current methods using PSNR(peak signal to noise ratio) as a criterion of judgment.