• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.685-686
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• 2016

엑스선 투시촬영장치와 같은 의료용 동영상의 잡음 제거에 있어서 시공간 잡음제거 알고리즘을 제안한다. 제안된 알고리즘에서는 무한 충격 응답 기반 시간 영역 잡음 제거 얄고리즘을 도입하여 움직임이 적은 영역에서는 자연스러운 잡음 제거가 가능하며 움직임이 많은 영역에서는 연산량 측면에서 효율성을 고려하여 지역적 평균 필터 기반 공간 잡음 제거 알고리즘을 적용하여 움직임에 의한 흐려짐 열화 현상을 최소화 하면서 잡음 제거를 수행하였다.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.107-110
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• 2000

최근 이동전화의 사용이 급격히 확산됨에 따라 편이성과 안정성의 문제로 핸즈프리 전화통신의 필요성이 대두되고 있다. 핸즈프리 통신상황의 경우 근거리에 위치한 스피커와 마이크로폰의 커플링에 의해 발생하는 음향반향과 차량내에 존재하는 배경잡음에 의하여 통화 품질이 크게 저하되는 문제가 발생한다. 본 논문에서는 차량내에서 핸즈프리 전화통신에 적합한 음향반향과 잡음제거 시스템을 제안하였다. 특히, 안정적인 음향반향제거 성능을 얻기 위하여 두 개의 평균 상호상관도를 이용한 동시통화검출 알고리즘을 제안하였다. 음향반향제거를 위해서는 NLMS 알고리즘에 의해 구동되는 제한된 차수의 적응반향제거기법을 사용하였으며, 잔여 반향 및 배경 잡음제거를 위해 IS-127 EVRC음성 부호화기의 잡음제거 방식을 사용하였다. 제안된 시스템은 16비트 고정소수점 DSP인 OAK DSP를 이용하여 약23.17MIPS의 연산량으로 실시간 구현되었다.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1127-1139
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• 2013

In the realization of obtained image by various visual equipments, the addition of noise to the original image is a common phenomenon and the occurrence of the noise is practically impossible to prevent completely. Thus, the noise detection and reduction is an important foundational purpose. In this study, we detect the orientation about feature of images and estimate the level of noise variance based on the measurement of the relative proportion of the noise. Also, we apply the estimated level of noise to the sigma filter on noise reduction algorithm. And using the orientation about feature of images by weighted value, we propose the effective algorithm to eliminate noise. As a result, the proposed statistical noise reduction methodology provides significantly improved results over the usual sigma filtering and regardless of the estimated level of the noise variance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1C
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• pp.96-102
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• 2010

This paper proposes a new adaptive algorithm to cancel the acoustic feedback and noise signals in the digital hearing aids. The proposed algorithm improves its convergence performances by canceling the speech signal from the residual signal using two microphones. The feedback canceller firstly cancels the feedback signal among the mic signal, and then it is reduced the noise using the beamforming method. To verify the performances of the proposed algorithm, the simulations were carried out for some cases. As the results of simulations, it was proved that the feedback canceller and the noise canceller advance about 14.43 dB for SFR, 10.19 dB for SNR respectively during speech, in the case of using the new algorithm.

• The Journal of the Acoustical Society of Korea
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• v.12 no.5
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• pp.54-63
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• 1993

적응 능동 잡음제거를 위한 새로운 방식을 기술했으며, 잡음원이 존재하는 환경에서 물리적인 잡음 제거를 하는데 목표를 두었다. 기존의 시스템 식별 방식과 달리 적응 예측기를 사용하였으며 신호를 검출하는데 쓰이는 마이크를 하나로 구성하였다. 잡음 신호 자체를 예측함으로써 적극적인 대처를 할 수 있으며 적응 알고리즘은 한번만 사용되고 적응 제어형 시스템 식별 방식에서 필요로 하는 피드백 항을 제거시킴으로써 시스템을 간략화시켰다. 컴퓨터 모의 실험 결과를 통하여 제안한 방식이 주기성을 갖거나 혹은 대역 제한된 잡음에 대해서 매우 유용함을 보였다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2013.06a
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• pp.325-328
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• 2013

본 논문에서는 ToF(Time-of-Flight) 카메라의 거리 잡음을 제거하는 방법으로 거리와 진폭에 따른 거리 잡음 모델링을 이용한 적응적인 SUSAN(Smallest Univalue Segment Assimilating Nucleus) 필터를 제안한다. ToF 카메라의 거리 잡음 제거를 위해서 기존에 제안된 여러 가지 방법들은 거리 잡음의 특성을 고려하지 않거나 진폭에 따른 거리 잡음의 특성만을 고려하였다. 하지만 실제 ToF 카메라의 거리 영상에 포함되는 거리 잡음은 진폭과 거리에 따라서 변화하기 때문에 거리와 진폭을 모두 고려한 거리 잡음 모델링이 필요하다. 따라서 제안하는 방법은 우선 거리와 진폭의 변화에 따른 ToF 카메라의 거리 잡음 특성을 모델링 한다. 이후 제안하는 방법은 생성된 거리 잡음 모델에 의해 인자가 결정되는 적응적 SUSAN 필터를 이용하여 ToF 카메라의 거리 영상의 잡음을 제거한다. 실험 결과 제안하는 방법은 기존의 ToF 거리 영상의 거리 잡음제거 방법에 비해 보다 효과적으로 거리 영상의 잡음을 제거하면서 디테일을 잘 보존하였다.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.9
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• pp.1293-1298
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• 2013

This paper proposes a noise reduction algorithm using Wiener filter to remove the noise components from the noisy speech in order to improve the speech signal. The proposed algorithm first removes the noise spectrums of white noise from the noisy signal based on the noise reshaping and reduction method at each frame. And this algorithm enhances the speech signal using Wiener filter based on linear predictive coding analysis. In this experiment, experimental results of the proposed algorithm demonstrate using the speech and noise data by Japanese male speaker. Based on measuring the spectral distortion (SD) measure, experiments confirm that the proposed algorithm is effective for the speech by contaminated white noise. From the experiments, the maximum improvement in the output SD values was 4.94 dB better for white noise compared with former Wiener filter.

• Geophysics and Geophysical Exploration
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• v.15 no.4
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• pp.199-208
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• 2012

High-amplitude swell noises (HASN) are very difficult to eliminate from the marine seismic data. In this paper, we applied F-X filter and median filter in order to suppress HASN. Test data have been acquired on the northern offshore of the South Shetland Islands in December, 2010. Parts of data have been contaminated by HASN caused by bad weather during the cruise. We applied F-X filter and median filter to test data with HASN. After F-X filtering, most of non-coherent noises and small-amplitude swell noises are eliminated effectively but HASN are still remained significantly. With median filter, HASN was suppressed better than F-X filter, however some of non-coherent noises are still remains. We applied a cascade of two filters and results show HASN and non-coherent noises are suppressed effectively. After the cascade of two filtering, it is possible to define reflection layers clearly on the velocity spectrum and to produce better stacked section with a good signal-to-noise ratio.

• The Journal of the Acoustical Society of Korea
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• v.21 no.6
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• pp.576-584
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• 2002

This paper proposes a new denosing method using wavelet packet, to reject unknown external noise and white gaussian ambient noise for measuring the transient noise which is one of the important elements for ship classification. The previous denosing method applied the same wavelet threshold at each node of multi-single sensors for rejecting white noise is not adequate in the underwater environment existing lots of external noises. The proposed algorithm of this paper applies a modified soft-threshold to each node according to the discriminated threshold so as to reject unknown external noise and white gaussian ambient noise. It is verified by numerical simulation that the SNR is increased more than 25㏈. And the simulation results are confirmed through sea-trial using multi-single sensors.

• Journal of Korean Ophthalmic Optics Society
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• v.17 no.2
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• pp.203-207
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• 2012

Purpose: Electroretinogram(ERG) signal noise as well as conducting other bio-signal measurement were generated. It was intened to enhance the accuracy of retinal-related diagnosis with removing signal noise. Methods: Sampling signal was made with generating 60 Hz noise and white noise. The noise were removed using wavelet transforms and bandpass filter. De-noising frequency was compared with Fourier transform spectrum. Removed noises were compared numerically using SNR(signal to noise ratio). Results: The result compared Fourier transform spectrum was showed that 60 Hz noise removed completely and most of white noise was removed by wavelet transforms. 60 Hz and the white noise remained using bandpass filters. The result compared SNR showed that wavelet transforms was 22.8638 and bandpass filter was 4.0961. Conclusions: Wavelet transform showed less signal distortion in removing noise. ERG signal is expected to improve the accuracy of retinal-related diagnosis.