• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.945-951
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• 2007

Noise cancellation is essential for the devices which use speech as an interface. In real environments, speech quality and recognition rates are degraded by the auditive noises coming near the microphone. In this paper, we propose a noise cancellation algorithm using stereo microphones basically. The advantage of the use of multiple microphones is that the direction information of the target source could be applied. The proposed noise canceller is based on the Wiener filter. To estimate the filter, noise and target speech frequency responses should be known and they are estimated by the spectral classification in the frequency domain. The performance of the proposed algorithm is compared with that of the well-known Frost algorithm and the generalized sidelobe canceller (GSC) with an adaptation mode controller (AMC). As performance measures, the perceptual evaluation of speech quality (PESQ), which is the most widely used among various objective speech quality methods, and speech recognition rates are adopted.

• Journal of Digital Convergence
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• v.11 no.7
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• pp.135-140
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• 2013

Noise estimation and detection algorithm to adapt quickly to changing noise environment using the LMS Filter. However, the LMS Filter for noise estimation for a certain period of time and need time to adapt. If the signal changes occur, have the disadvantage of being more adaptive time-consuming. Therefore, noise removal method is proposed to a frame basis AELMS Filter to compensate. In this paper, we split the input signal on a frame basis in noisy environments. Remove the LMS Filter by configuring noise predictions using the mean and variance. Noise, even if the environment changes fast adaptation time to remove the noise. Remove noise and environmental noise and speech input signal is mixed to maintain the unique characteristics of the voice is a way to reduce the damage of voice information. Noise removal method using a frame basis AELMS Filter To evaluate the performance of the noise removal. Experimental results, the attenuation obtained by removing the noise of the changing environment was improved by an average of 6.8dB.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.683-686
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• 2010

본 논문은 영상 내에서 영역을 분할하여 영상 잡음을 효과적으로 제거하는 기법을 제안한다. 제안한 방법을 통해 잡음 영상을 영역 분할 경우 잡음부분까지 영역 분할되는 문제가 발생하기 때문에 잡음 영상을 저대역(Low-pass) 필터를 통과함으로써 잡음을 최소화한다. 저대역 필터를 통과한 영상에서 에지를 추출하여 비정상적인 에지의 추출을 방지함으로써 영상이 가진 근본적인 에지를 정확하게 추출한다. 획득한 에지 정보를 바탕으로 각 영역간의 히스토그램의 평균 오차를 이용하여 영역을 분할한다. 분할된 영역은 각 영역별로 저대역(Low-pass) 필터를 통과시킴으로써 영역에 맞는 잡음 제거를 통해서 더욱 빠르고 효과적으로 제거한다. 본 논문의 방법은 기존의 학습을 통한 잡음 제거 방법과 다르게 학습 시간이 요구되지 않으며, Non-local Means의 방법과 다르게 큰 연산량을 요구하지 않기 때문에 유사한 성능으로 빠른 잡음 제거를 할 수 있다.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.6B
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• pp.760-766
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• 2001

본 논문에서는 차량내 핸즈프리 전화통신을 위한 음향 반향 및 배경 잡음 제거기를 제안한다. 제안한 시스템은 새로운 잔여 반향 제거 기법과 실시간 구현에 적합한 동시통화 검출기를 포함한다. 잔여 반향 제거에서는 근단화자가 없는 구간에 대하여 선형 예측기를 이용하여 잔여 반향 신호의 인접 샘플간의 상관도를 제거하여 잡음 제거기의 입력으로 사용한다. 잔여 반향 신호의 음성특성을 제거함으로써 잡음 제거기를 이용하여 배경 잡음과 더불어 잔여 반향의 전력을 효과적으로 줄일 수 있다. 제안된 시스템에서는 상용 저전송률 음성부호화기와의 결합을 고려하여 IS-127(EVRC)에 포함되어 있는 잡음 제거기를 사용하였다. 90 km/h로 정속 주행하는 차내의 핸즈프리 환경에서 제안된 시스템은 30 dB이상의 간섭신호 제거 성능을 보였다. 제안된 시스템은 16비트 고정 소수점 연산을 하는 저가의 DSP를 이용하여 실시간 구현되었다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.5
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• pp.1227-1232
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• 2013

Recently, the expectation of quality about images over the increasing demand of digital devices is increasing with the development of the technology of the digital. But the images are degraded by a variety of causes, and the main reason is the noises. Therefore, the necessity of denoising comes to the fore, and the research for denoising is progressing dynamically. The images are mainly degraded by AWGN(additive white Gaussian noise), and the characteristics of denoising of existing methods such as mean filter are insufficient. In this paper, an algorithm combined by the spatial weighted filter and the modified adaptive weighted filter is proposed in order to effectively remove the AWGN. In the simulation result, the proposed algorithm showed excellent denoising capabilities.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.2 s.95
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• pp.116-122
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• 1999

저차 동적계(특히 카오스계)에서 측정한 시계열의 잡음을 제거하기 위해서 SVD(Singular Value Decomposotion)을 이용한 새로운 간편하고 매우 효과적인 새로운 잡음 제거법이 소개되었다. 이 방법은 위상궤적(phase portraint)을 재구성하는데 중점을 두었으며, 궤적행렬(trajectory matrix)을 구성하는데 그 기본을 두었다. 이 궤적행렬에 SVD를 반복적으로 사용하여 신호와 잡음을 분리하였다. 이 방법은 Duffing계에서 측정한 잡음이 섞인 카오스 신호에 적용되었으며, 또한 실험에 의한 진폭변조된 신호에도 적용되었다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2021.06a
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• pp.61-62
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• 2021

본 논문에서는 조건부 wavenet을 이용한 음성 신호의 잡음 제거 기술을 제안한다. 기존의 음성 신호 잡음 제거 기술은 스펙트로그램을 기반으로 발전되어 왔으나, 잡음으로 인해 변형된 원음의 위상 정보를 복원할 수 없는 문제점을 가진다. 이를 해결하기 위해 시간 영역에서 전 과정을 실행하는 기계학습 모델인 wavenet을 사용하여 음성 신호의 잡음을 제거하는 방법을 제안한다. 특히, 잡음 종류를 조건으로 입력하여 성능 향상을 얻도록 한다. 성능 평가를 통하여 제안 방법이 시간 영역에서 잡음을 감소시킬 수 있음을 확인하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.411-413
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• 2013

Image signal processing is applied in different areas due to diffusion of smart phone, computer, multimedia etc. However, image most is damaged by impulse noise, and the need of denoising technology for improvement of image quality is coming to the fore. The existing methods for denoising such as mean filter and median filter, but they represent poor denoising. Therefore, the removes impulse noise, this paper proposed the modified mean filter algorithm using standard deviation, and as a simulation result, the proposed method showed excellent denoising capabilities to the existing methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.255-257
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• 2018

Recently, as the frequency of use of video media increases in various fields, the importance of signal processing is increasing. However, many kinds of noise are generated in the transmission and reception process and affect the information of the signal. For this reason, the noise removal is essential as a preprocessing process. In this paper, we propose an algorithm to remove mixed noise of impulse noise and AWGN. The proposed algorithm restores the image through noise determination and pixel change for efficient noise removal. Unlike the conventional method, noise is removed by minimizing both noise effects. Simulation showed excellent noise removal characteristic results were compared and analyzed using the PSNR for such decisions.