• The Korean Journal of Applied Statistics
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• v.31 no.5
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• pp.555-572
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• 2018

Noise reduction processes that reduce or eliminate noise (caused by a variety of reasons) in noise contaminated image is an important theme in image processing fields. Many studies are being conducted on noise removal processes due to the importance of distinguishing between noise added to a pure image and the unique characteristics of original images. Adaptive filter and sigma filter are typical noise reduction filters used to reduce or eliminate noise; however, their effectiveness is affected by accurate noise estimation. This study generates a distribution of noise contaminating image based on a Dirichlet normal mixture model and presents a Bayesian approach to distinguish the characteristics of an image against the noise. In particular, to distinguish the distribution of noise from the distribution of characteristics, we suggest algorithms to develop a Bayesian inference and remove noise included in an image.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.151-156
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• 2012

In this paper robust nonlinear image denoising algorithms are introduced for the distribution which is Gaussian in the center and Laplacian in the tails. The distribution is known as the least favorable ${\epsilon}$-contaminated normal distribution that maximizes the asymptotic variance. The proposed filter proves to be the maximum likelihood estimator under the heavy-tailed Gaussian noise environments. It is optimal in the respect of maximizing the efficacy under the above noise environment. Another filter for reducing impulsive noise is proposed by mixing with the myriad filter to propose an amplitude-limited myriad filter. Extensive experiment is conducted with images corrupted with ${\alpha}$-stable noise to analyze the behavior and performance of the proposed filters.

• The Journal of the Acoustical Society of Korea
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• v.18 no.5
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• pp.35-43
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• 1999

In this paper, a new robust adaptive algorithm and a post-processing method are proposed to improve the performance of AEC without computational burden. Its step-size is normalized by the sum of the powers of the reference input signal and the desired signal. When the near-end speaker's speech and noise are applied into the microphone, the step-size becomes small and the misalignment of coefficients are reduced. To reduce the residual echoes, a new post-processing method, which is co-operated with the proposed noise-robust adaptive algorithm, is proposed in this paper. The method is based on the correlation of the desired signal and the estimation error signal. The residual echoes are attenuated as proportional to the correlation normalized with the power of desired signals. The normalized correlation plays a role as Wiener filter for residual echoes. In the double-talk situation, the estimation error signals, that are residual echoes, dominantly include the near-end speaker's speech and the normalized correlation closes to 1. Therefore, the near-end speaker's speech can be transmitted without being attenuated. When the desired signals consists of only the acoustic echoes, the residual echoes are mostly attenuated and canceled by the proposed post-processor. The computation of AEC using the proposed post-processor is comparable to NLMS algorithm.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2006.07a
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• pp.587-587
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• 2006

• The Journal of the Acoustical Society of Korea
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• v.15 no.4
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• pp.83-92
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• 1996

This paper describes Lombard effect compensation and noise suppression so as to reduce speech recognition error in noisy environments. Lombard effect is represented by the variation of spectral envelope of energy normalized word and the variation of overall vocal intensity. The variation of spectral envelope can be compensated by linear transformation in cepstral domain. The variation of vocal intensity is canceled by spectral magnitude normalization. Spectral subtraction is use to suppress noise contamination, and band-pass filtering is used to emphasize dynamic features. To understand Lombard effect and verify the effectiveness of the proposed method, speech data are collected in simulated noisy environments. Recognition experiments were conducted with contamination by noise from automobile cabins, an exhibition hall, telephone booths in down town, crowded streets, and computer rooms. From the experiments, the effectiveness of the proposed method has been confirmed.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.34-36
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• 2001

본 논문에서는 모델 기반의 잡음 보상 방법인 PMC (parallel model combination)를 온라인상에서 적용하는 방법에 관해 논한다. PMC는 파라미터 보상시 미리 계산된 잡음 모델을 필요로 하며 파라미터 보상에 많은 연산을 요구하므로 온라인으로 모델 파라미터를 보상하기가 어렵다. 본 논문에서는 이러한 문제를 해결하기 위해 기존에 제안된 온라인 모델 보상 방법을 살펴보고, 기존 방법에서 보상 시간 문제로 제외한 PMC의 공분산 보상을 비교적 적은 연산량으로 수행하여 인식성능을 더욱 향상시켰다. 고립 숫자음 인식시스템에 백색 잡음을 SNR 0, 5, 10 dB로 가산한 평가 자료로 실험한 결과, 제안한 방식은 PMC를 적용한 경우에 비해 모델 적응 시간은 적게 걸리면서도 기존의 온라인 모델 보상 방법에 비해 평균 10%의 인식률 향상을 보였다.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.10
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• pp.154-160
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• 1990

System modeling for Heterodyne/Coherent Optical BFSK receiver is described and its receiver performance is evaluated. Receiver performance is deteriorated due to both shot noise and laser phase nois. Therefore, to minimize these noise impacts PLL loop natural frequency is selected optimally. For different power penalty due to phase error, required phase error variance to achieve $BER=10^{-9}$, nomalized loop power, and laser linewidth/bit rate(${\Delta\nu}s/Rb$) are derived. For 0.5dB power penalty, phase error variance=0.035(${rad^2}$), photon numbers=20.0, nomalized loop power = $3.8{\times}10^{-3}$(electron/s per herz), and ${\Delta\nu}s/Rb=5.24{\times}10^{-3}$ are obtained.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.9
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• pp.995-1000
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• 2016

The maximum cross-correntropy (MCC) algorithm with a set of random symbols keeps its optimum weights undisturbed from impulsive noise unlike MSE-based algorithms and its main factor has been known to be the input magnitude controller (IMC) that adjusts the input intensity according to error power. In this paper, a normalization of the step size of the MCC algorithm by the power of IMC output is proposed. The IMC output power is tracked recursively through a single-pole low-pass filter. In the simulation under impulsive noise with two different multipath channels, the steady state MSE and convergence speed of the proposed algorithm is found to be enhanced by about 1 dB and 500 samples, respectively, compared to the conventional MCC algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.1
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• pp.1-7
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• 2017

The maximum zero error probability (MZEP) algorithm outperforms MSE (mean squared error)-based algorithms in impulsive noise environment. The magnitude controlled input (MCI) which is inherent in that algorithm is known to plays the role in keeping the algorithm undisturbed from impulsive noise. In this paper, a new approach to normalize the step size of the MZEP with average power of the MCI is proposed. In the simulation under impulsive noise with the impulse incident rate of 0.03, the performance enhancement in steady state MSE of the proposed algorithm, compared to the MZEP, is shown to be by about 2 dB.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2006.05a
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• pp.111-114
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• 2006

비백색잡음(non-white noise)인 잔향(reverberation)이 신호탐지(signal detection)의 주 방해신호인 천해 능동소나(active sonar) 환경에서의 표적탐지는 선백색화기(pre-whitening filter)를 사용하여 수신신호를 백색화한 후 백색잡음에서 최적 탐지기(optimum detector)인 정합필터를 사용한다. 그러나 이 방법은 잔향이 비정상(non-stationary) 특성을 가지기 때문에 구현이 매우 힘들다. 기존의 연구에 따르면 이러한 잔향은 지역적 정상상태(local stationary)라고 가정할 수 있다. 본 논문에서는 먼저 잔향신호의 지역적 정상상태의 범위를 추정(estimation)하고, 이 추정을 바탕으로 천해와 같은 비백색 잔향신호 환경에서 선백색화 블럭 정규화 정합필터(pre-whitening block normalized matched filter)의 성능을 개선할 수 있는 선백색화 기법을 제안하였다. 제안된 잔향신호의 백색화 기법은 표적신호 전 후의 잔향신호를 사용하여 처리블록(processing block)을 백색화하기 때문에 기존의 백색화 기법보다 우수한 성능을 보였다. 제안된 백색화 기법을 이용한 탐지기의 성능을 평가하기 위해 우리나라 인근해역에서 실측된 데이터를 이용하여 컴퓨터 모의실험을 수행하였다. 모의실험 결과 제안된 기법을 사용한 탐지기는 기존의 백색화 기법을 사용한 탐지기보다 우수한 탐지성능을 보였다.