• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.477-481
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• 2009

In this paper the process of transmitting images signal restore to image corrupted by impulse noise proposed switching mean filter. these filter is differential size using the two state noise detection distinguishes noise pixel and noise free pixel. Follow the detected impulse noise density in the image remove the impulse noise using switching mean filter these substituted pixel in order to non-recursive and recursive form from control process of the next pixel comes to be used with neighbor pixel process. Through the simulation, we compared with the existing methods and capabilties.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.477-478
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• 2011

전기, 전자분야에 반도체가 폭넓게 사용됨에 따라 발 변전소에서 Noise에 의한 보호계전기 오동작 사례가 늘어나고 있어, 이것을 효과적으로 차단하고 설비의 오동작을 예방할 수 있는 필터개발이 필요 하였다. 현재 시중에서 사용하고 있는 Ferrite Filter는 일반 가전 및 OA를 대상으로 개발하였기 때문에 송변전계통의 변전소에서 발생하는 Noise와 차단 영역이 다르다. 따라서 송변전설비 보호계전기의 오동작원인을 분석하고, 변전소에서 발생하는 Noise의 형태를 측정하여 그것을 차단하기에 적합한 Clamp형의 Ferrite Filter를 개발하였다. Ferrite Filter는 재질에 따라 고주파 차단 영역이 결정된다. 일반적인 전자설비에 사용하는 니켈계(Ni-Zn) 재질의 Filter는 수MHz~수GHz 영역이며, 변전소에 주로 발생하는 고주파 수KHz~수MHz 영역은 망간계(Mn-Zn) 재질을 혼합하여 만들었다. 개발한 Filter의 성능 확인을 위해 공인시험기관인 KERI(한국전기연구원)에서 다양한 형태로 고주파 차단 특성 시험을 시행한 결과, 망간계와 니켈계 Ferrite Filter를 직렬로 설치함으로서 Noise를 효과적으로 차단함을 확인 하였고 5개소에 2개월간시범적용을 통하여 그 성능을 검증하였다. 본 연구결과는 Clamp형 Ferrite Filter의 기술적 한계로 여겨졌던 고주파 차단특성을 발변전소 등의 전력설비에서 발생하는 대역까지 확대하였으며, 경제적으로도 기존의 L-C Filter 대비 약 4%의 비용으로 설치할 수 있어 그 비용을 획기적으로 절감하였고, 설비의 정지 없이 언제든지 간편하게 설치할 수 있어 현장에서 적용하기에 매우 유용하다. 그 성능을 지속적으로 향상시켜 많은 분야에서 활용할 수 있도록 추가적인 연구개발이 필요할 것으로 판단된다.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.260-263
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• 2000

A technique that uses linear prediction to achieve noise reduction in a voice signal which has been mixed with an ambient noise (Signal to Noise (S-N) ratio = about 0dB) is proposed. This noise reduction method which is based on the linear prediction estimates the voice spectrum while ignoring the spectrum of the noise. The performance of the noise reduction method is first examined using the transversal linear predictor filter. However, with this method there is deterioration in the tone quality of the predicted voice due to the low level of the S-N ratio. An additional processing circuit is then proposed so as to adjust the noise reduction circuit with an aim of improving the problem of tone deterioration. Next, we consider a practical application where the effects of round on errors arising from fixed-point computation has to be minimized. This minimization is achieved by using the lattice predictor filter which in comparison to the transversal type, is Down to be less sensitive to the round-off error associated with finite word length operations. Finally, we consider a practical application where noise reduction is necessary. In this noise reduction method, both the voice spectrum and the actual noise spectrum are estimated. Noise reduction is achieved by using the linear predictor filter which includes the control of the predictor filter coefficient’s update.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.1
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• pp.179-184
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• 2019

In this paper, we propose a design method of Active Noise Control (ANC) that reduces perceived level of the residual noise. A FELMS (Filtered-E Least Mean Squares) algorithm is used for the ANC system and the NC (noise criteria) is applied as an evaluation criterion of the residual noise. With this structure, we present the allowable spectral shape of the noise shaping filter that minimizes the NC index within the effective operating frequency band of the ANC, and showed that the filter satisfying in the criterion has a lower NC value than the psychoacoustic-based filter used in the previous studies.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.1
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• pp.232-238
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• 2013

This paper study the position estimation of MBK system according to the non-linear filter for non-Gaussian noise in underwater sensor networks. In the filter to estimate location, recently, the extended Kalman filter (EKF) and particle filter are getting attention. EKF is widely used due to the best algorithm in the Gaussian noise environment, but has many restrictions on the usage in non-Gaussian noise environment such as in underwater. In this paper, we propose the improved One-Dimension Particle Filter (ODPF) using the distribution re-interpretation techniques based on the maximum likelihood. Through the simulation, we compared and analyzed the proposed particle filter with the EKF in non-Gaussian underwater sensor networks. In the case of both the sufficient statistical sample and the sufficient calculation capacity, we confirm that the ODPF's result shows more accurate localization than EKF's result.

• The Journal of the Acoustical Society of Korea
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• v.31 no.1
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• pp.29-38
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• 2012

This paper presents a transient noise reduction system in a speech signal. The proposed transient noise reduction system utilizes a median filter to reduce the transient noise. Since the median filter can distort speech during the noise reduction, a long-term prediction (LTP) filter is adopted as a pre-processor to minimize speech distortion. The speech information preserved by the LTP filter is re-synthesized after reducing the noise. This paper verifies the weakness of a linear prediction (LP) filter and the superiority of the LTP filter for preserving the speech component in transient noise presence environment. Applying the proposed system, the signal-to-noise ratio (SNR) of output is improved by 8dB in both speech and noise presence region, and PESQ score is increased by 1 point comparing with noisy input.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.434-436
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• 1992

In this paper, we propose a new multilevel nonlinear filter for simultaneous edge detection and noise suppression, which we call a order statistic-median hybrid(OMH) filler. The median-related filters cause an edge shift in the presence of an impulse near the edge. The proposed filter reduces such edge shifting while suppressing impulsive as well as nonimpulsive noise. We show that at the noisy edge point the OMH filter is substantially superior to the median filter, the $\alpha$-TM filter and the STM filter[I] in two respects: (a) the output bias error and (b) the output mean square error. Test results confirm that the OMH filter is robust in preserving sharp edges, inhibiting edge shifting, and suppressing a wide variety of noise. The structure for the OMH filter integrated circuit is also described.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.1
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• pp.193-204
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• 1997

In this research we propose the design of the Order Statistic-Adaptive Weighted Average Hybrid(OS-AWAH) filter which can suppress noise from the corrupted image sequence effectively while preserving the image structure. The proposed filter combines the desirable properties of the order static based spatial filter which can preserve the image structure while reducing noise and the adaptive weighted average based temporal filter which can adapt the filtering weights according to the amount of motion without motion estimation. Performance characteristics of the OS-AWAH filter in noisy sequences containing moving step edges are investigated throuth computer simulations and compared with the median based filters such as 3-D WM(weighted median) filter, MMF (multistage median filter), ADCWM(adaptive directional center weighted median) filter. The visual evaluations are also carried out by applyin gthe filters to the real images. The statistical analysis and experimental reslts show that the OS-AWAH filter is effective in preserving image structures while suppressing noise effectively without motion compensation preprocessing.

• The Transactions of the Korea Information Processing Society
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• v.6 no.10
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• pp.2830-2837
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• 1999

Image processing steps are consist of image acquisition, preprocessing, region, segmentation and recognition. But image corrupted commonly by noise reduction methods, many filters were proposed like mean filter, median filter, weighted median filter, Cheikh filter, and Kyu-cheol lee filter as spatial noise reduction filtering. We propose a new edge detection algorithm so that we find out edge existence and nonexistence. In non-edge area, we selectively apply weighted median filter based upon using information of difference value between weighted median filter's value and center pixel's value. As a result, we finally prove a better performance of noise reduction by applying adaptive weighted median filter and improvement of processing time through using simple algorithm.

• Journal of Korea Multimedia Society
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• v.17 no.8
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• pp.923-936
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• 2014

Images can be contaminated with different types of noise, for different reasons. The neighborhood averaging and smoothing by image averaging are the classical image processing techniques for noise removal. The classical spatial filtering refers to the aggregate of pixels composing an image and operating directly on these pixels. To reduce or remove effectively noise in image sequences, it usually needs to use noise reduction filter based on space or time domain such as method of spatial or temporal filter. However, the method of spatial filter can generally cause that signals of objects as the target are also blurred. In this paper, we propose temporal filter using the piece-wise quadratic function model and enhancement algorithm of image quality for the performance improvement of target detection and tracking by heterogeneous noise reduction. Image tracking simulation that utilizes real IIR(Imaging Infra-Red) images is employed to evaluate the performance of the proposed image processing algorithm.