• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.671-673
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• 2016

In image data, noise occurs due to various external factors in the process of obtaining and transmitting. There are various types of noise according to the cause and form and research to remove this noise is being continued. Therefore the study suggested a way to filter to restore images damaged by salt and pepper noise which preserves non-noise signal and processes noise signal by expanding mask size according to the local mask noise density. In addition, as an objective evaluation standard of improvements, the study used PSNR(peak signal to noise ratio) to compare with previous methods.

• Journal of radiological science and technology
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• v.30 no.4
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• pp.329-334
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• 2007

This paper is for investigation of the noise reduction effect all 20 filters by combining Low Pass Filter(LPF) 5 kinds, High Pass Filter(HPF) 4 kinds, Median Filter(MF) 11 kinds. Noise is added to reduce noise and minimize the quality degradation in medical imaging system. We also compared Peak Signal to Noise Ratio(PSNR), Mean Square Error(MSE) for all the combinations of different filters. As a result, noise decrease appeared in the LPF3*3#1 + HPF3*3#1 + Vertical3*1 of highest filter. We confirmed noise reduction effect by applying the proposed filter combination in many fields of medical imaging applications.

• Journal of Sensor Science and Technology
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• v.9 no.4
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• pp.316-326
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• 2000

A new signal processing algorithm for white light interferometry has been proposed and investigated theoretically. The goal of the algorithm is to determine the absolute optical path length of an interferometer with very high precision (<< one optical wavelength). The algorithm features cross-correlation of interferometer fringe scans and hypothesis testing. The hypothesis test looks for a zero order fringe peak candidate about which the cross-correlation is symmetric minimizing the uncertainty of misidentification. The shot noise limited performance of the proposed signal processing algorithm has been analyzed using computer simulations. Simulation results were extrapolated to predict the misidentification rate at Signal to-Shot noise ratio (SNR) higher than 31 dB. Root-mean-square phase error between the computer-generated zero order fringe peak and the estimated zero order fringe peak has been calculated for the changes of three different parameters (SNR, fringe scan sampling rate, coherence length of light source). Results of computer simulations showed the ability of the proposed signal processing algorithm to identify the zero order fringe peak correctly. The proposed signal processing algorithm uses a software approach, which is potentially inexpensive, simple and fast.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.953-955
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• 2016

Degradation is occurred in the process of the signal transmission in the image processing system due to various reasons. Degradation is noise addition in the image signal and the representative one to cause degradation is salt and pepper noise. Therefore, image restoring filter was suggested in this article to apply and process weighted value by the changes of each directional pixel upon breakdown of local mask with 8 directions in order to restore the damaged image in the environment of salt and pepper noise. In addition, peak signal to noise ratio (PSNR) was used to compare the existing method as the objective determinant standard of the improvement effect.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.346-349
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• 2017

Digital image processing is widely used in a variety of areas, and noise elimination is used as the preprocessing in all the image processing processes. Degradation is occurred in the image data due to multiple reasons. Degradation is to add the noise in the image signal, and salt and pepper noise is the representative one to cause degradation. Therefore, image restoration algorithm was proposed to process with histogram weight filter and median filter by the noise density of local mask to restore the damaged image in the salt and pepper noise environment, in this article. In addition, it was compared with the existing methods using peak signal to noise ratio(PSNR) as the objective determination factor of improvement effect.

• Bulletin of the Korean Chemical Society
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• v.24 no.7
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• pp.967-970
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• 2003

A new modified singular value decomposition method, piecewise polynomial truncated SVD (PPTSVD), which was originally developed to identify discontinuity of the earth's radial density function, has been used for large solvent peak suppression and noise elimination in nuclear magnetic resonance (NMR) signal processing. PPTSVD consists of two algorithms of truncated SVD (TSVD) and L₁ problems. In TSVD, some unwanted large solvent peaks and noise are suppressed with a certain soft threshold value, whereas signal and noise in raw data are resolved and eliminated in L₁ problems. These two algorithms were systematically programmed to produce high quality of NMR spectra, including a better solvent peak suppression with good spectral line shapes and better noise suppression with a higher signal to noise ratio value up to 27% spectral enhancement, which is applicable to multidimensional NMR data processing.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.4
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• pp.287-293
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• 2004

This paper proposes an efficient motion compensation algorithm for video sequences with brightness variations. In the proposed algorithm, the brightness variation parameters are estimated and local motions are compensated. To detect the frame with large brightness variations, we employ the frame classification based on the cross entropy between histograms of two successive frames, which can reduce the computational redundancy. Simulation results show that the proposed method yields a higher peak signal to noise ratio (PSNR) than that of the conventional methods, with a low computational load, when the video scene contains large brightness changes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.798-800
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• 2014

In recent years, according to the improvement of Digital image technology have been recently developed most of communication technology from multimedia communication service as well as image data transmission. But In the process of storing and transmitting noise is still generated in noise and the image degrades rapidly quality of a lot of image impulse noise. To eliminate this noise, SMF, CWMF, SWMF etc. The filters have been proposed to interfere with the noise characteristics of the filter are somewhat sufficient. Therefore, in this paper, in order to remove impulse noise is proposed a modified median filter. And impulse noise removal algorithms to confirm the existed PSNR(peak signal to noise ratio) from using conventional methods were compared.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.10
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• pp.2447-2453
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• 2013

The digital images are being degraded by noise in the process of acquisition, storage and transmission, Gaussian or impulse noise is the representative noise. Meanwhile, the image has lots of tendency to be degraded by complex noise, so various researches are being conducted for reducing these complex noise. In this paper, to remove complex noise, the algorithm processed by modified switching median filter and modified adaptive weighted filter according to the result after judging the kinds of noise is proposed. In the simulation result, excellent denoising capabilities. Furthermore, we compared proposed algorithm with existing methods for objective judgement, and PSNR(peak signal to noise ratio) is used by the criterion of judgement.

• 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.