• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.3
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• pp.598-604
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• 2012

Image signal is corrupted by various noises in image processing, many studies are being accomplished to restore those images. In this paper, we proposed a cascade filter algorithm for removing random valued impulse noise. The algorithm consists two steps that noise detection and noise elimination. Variance of filtering mask and center pixel variance are calculated for noise detection, and the noise pixel is replaced by estimated value which first apply switching self adaptive weighted median filter and finally processed by modified weight filter. Considering the proposed algorithm only remove noise and preserve the uncorrupted information that the algorithm can not only remove noise well but also preserve edge.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.6
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• pp.722-728
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• 2020

Digital image processing has been applied in a wide range of fields due to the development of IoT technology and plays an important role in data processing. Various techniques have been proposed to remove such noise, but the conventional impulse noise canceling methods are insufficient to remove noise of edge components of an image, and have a disadvantage of being greatly affected by random impulse noise. Therefore, in this paper, we propose an algorithm that effectively removes edge component noise in random impulse noise environment. The proposed algorithm calculates the threshold value by determining the noise level and switches the filtering process by comparing the reference value with the input pixel value. The proposed algorithm shows good performance in the existing method, and the simulation results show that the noise is effectively removed from the edge of the image.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.47-54
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• 2005

In general, wavelet coefficients are composed of a few large coefficients and a lot of small coefficients. In this paper, we propose image denoising algorithm using Bernoulli-Gaussian mixture model based on sparse characteristic of wavelet coefficient. The Bernoulli-Gaussian mixture is composed of the multiplication of Bernoulli random variable and Gaussian mixture random variable. The image denoising is performed by using Bayesian estimation. We present an effective denoising method through simplified parameter estimation for Bernoulli random variable using local expected squared error. Simulation results show our method outperforms the states-of-art denoising methods when using orthogonal wavelets.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.27 no.1
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• pp.54-61
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• 2023

With the development of IoT technologies and artificial intelligent, diverse digital image equipments are being used in industrial sites. Because image data can be easily damaged by noise while it's obtained with a camera or a sensor and the damaged image has a bad effect on the process of image processing, noise removal is being demanded as preprocessing. In this thesis, for the restoration of image damaged by the noise of random impulse, a switching filter algorithm based on noise estimation was suggested. With the proposed algorithm, noise estimation and error distraction were carried out according to the similarity of the pixel values in the local mask of the image, and a filter was chosen and switched depending on the ratio of noise existing in the local mask. Simulations were conducted to analyze the noise removal performance of the proposed algorithm, and as a result of magnified image and PSNR comparison, it showed superior performance compared to the existing method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.10 no.1
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• pp.17-30
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• 1985

The error rate performances of digital modulation systems in fluenced by impulsive noise have been investigated and discussed in the enviroment of electromagnetic interference(EMI). Using the derived equations for the probabilities of error of L-level ASK, M-ary PSK, MSK, QAM, and APK signals, the error rate performance of each system has been evaluated and compared each other. The results show that, in the case of gaussian noise enviornment, PSK system is superior to the other systems and the digital amplitude modulation systems are inferior on the contrary. In the environment of impulsive noise, the MSK at low interfere level shows the best error rate performance but in the high level interferer environment, the PSK shows the best error rate performance. Also it is known that the digital amplitude modulation systems are scarcely influenced by the variation of interfere level.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.1
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• pp.263-267
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• 2011

This paper analyzed randomness characteristics of output data in generator based on hardware noise source. Also it is enhanced security randomness in the output stream of generator, which is applied on Laplacian filter. First it reviews criteria of randomness verification of output stream of hardware noise generator, and presents the enhanced results of output stream of generator, which is applied on Laplacian filter.

• Journal of Korea Multimedia Society
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• v.13 no.9
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• pp.1329-1336
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• 2010

Cellular Automata is a discrete dynamical system which natural phenomena may be specified completely in terms of local relation, can increase and decrease the difference of luminance locally according to transition rule by keeping the characteristic of target image. In this paper, we propose a noise reduction method by keeping the characteristic using transition rule of Cellular Automata, also we propose methods of effective transition rule, the selection of parameters, the selection of number of neighborhood pixels. For uniform distribution noise, Gaussian noise, impulse noise, we do an experiment on adaptive state using different mathematical operations and compare its results. It was confirmed that the proposed transition rule is based on fast convergence speed and has stabile results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.4
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• pp.1951-1956
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• 2013

Distribution-matching type algorithms based on a set of symbols generated in random order provide a limited performance under biased impulsive noise since the performance criterion for the algorithms has no variables for biased signal. For the immunity against biased impulsive noise, we propose, in this paper, a modified performance criterion and derived related blind algorithms based on augmented filter structures and the distribution-matching method using a set of random symbols. From the simulation results, the proposed algorithm based on the proposed criterion yielded superior convergence performance undisturbed by the strong biased impulsive noise.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.11
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• pp.2160-2169
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• 1994

Main components of phase time error of synchronous network are flicker noise and random walk noise. This paper describe computer simulation of clock error characterized by a statistical model recommended as a standard measure. Flicker noise sequences are generated from white noise sequences by means of a algorithm developed by Barnes. Random-walk noise sequence are obtained by integration of a white noise sequence. Especially for flicker noise, relation between stage number N, time constant ratio K and bandwidth of flicker noise generated was defined by using some examples.

• Journal of the Korea Convergence Society
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• v.13 no.1
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• pp.43-50
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• 2022

In this paper, it is shown how the performance of the monopulse algorithm in additive noise is evaluated. In the previous study, the performance analysis of the amplitude-comparison monopulse algorithm was conducted via the first-order and second-order Taylor expansion of four variables. By defining two new random variables from the four variables, it is shown that computational complexity associated with two random variables is much smaller than that associated with four random variables. Performance in terms of mean square error is analyzed from Monte-Carlo simulation. The scheme proposed in this paper is more efficient than that suggested in the previous study in terms of computational complexity. The expressions derived in this study can be utilized in getting analytic expressions of the mean square errors.