• Journal of the Korea Institute of Information and Communication Engineering
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• v.27 no.1
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• pp.54-61
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• 2023

With the development of IoT technologies and artificial intelligent, diverse digital image equipments are being used in industrial sites. Because image data can be easily damaged by noise while it's obtained with a camera or a sensor and the damaged image has a bad effect on the process of image processing, noise removal is being demanded as preprocessing. In this thesis, for the restoration of image damaged by the noise of random impulse, a switching filter algorithm based on noise estimation was suggested. With the proposed algorithm, noise estimation and error distraction were carried out according to the similarity of the pixel values in the local mask of the image, and a filter was chosen and switched depending on the ratio of noise existing in the local mask. Simulations were conducted to analyze the noise removal performance of the proposed algorithm, and as a result of magnified image and PSNR comparison, it showed superior performance compared to the existing method.

• The Journal of the Acoustical Society of Korea
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• v.29 no.2
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• pp.148-153
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• 2010

In speech signal processing, speech signal corrupted by noise should be enhanced to improve quality. Usually noise estimation methods need flexibility for variable environment. Noise profile is renewed on silence region to avoid effects of speech properties. So we have to preprocess finding voice region before noise estimation. However, if received signal does not have silence region, we cannot apply that method. In this paper, we proposed SNR estimation method for continuous speech signal. A Speech signal consists of Voice and Unvoiced Band in The MBE excitation model. And the energy of speech signal is mostly distributed on voiced region, so we can estimate SNR by the ratio of voiced region energy to unvoiced. We use the IMBE vocoder for the Voice or Unvoice band of segmented speech signal. Continuously we calculate the segmented SNR using that information and the energy of each band. And we estimate the SNR of continuous speech signal.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.5
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• pp.139-145
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• 2010

In this paper, we propose robust cell ID detection algorithm and SNR estimation algorithm applicable to mobile base station, which can be operated independently. The proposed cell ID estimation uses signal subspace to estimate cell IDs used in cell. The proposed SNR estimation algorithm uses number of noise subspace vectors and the corresponding eigen-vectors. Through the computer simulations, we showed that performance of the proposed cell ID detection and SNR estimation algorithms are superior to existing correlation based algorithms. Also we showed that the proposed algorithm is suitable to fast moving channel in high background noise and strong interference signal.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.11a
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• pp.321-324
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• 2011

본 논문에서는 contourlet 변환을 이용하여 잡음을 제거하는 방법을 제안한다. 영상 센서의 발전으로 이미지의 해상도가 좋아지는 반면 잡음에 민감해진다. 그러므로 이를 전처리 단계에서 처리해주는 것이 필요하다. 잡음은 주로 자연 영상의 윤곽선에서 민감하게 반응하기 때문에 고주파대의 잡음을 최대한 정확하게 제거하는 과정이 중요하다. Contourlet 변환은 기존의 wavelet 변환의 다중 스케일과 더불어 다양한 방향 필터뱅크를 이용하여 방향 성분에 대하여 풍부한 정보를 얻을 수 있는 변환이다. 영상의 화이트 가우시안 잡음을 제거하기 위해 contourlet 변환 영역에서의 계수를 이변수 가우스 확률 모델로 설정하고 Bayes 추정법을 사용한다. Bayes 추정법에 필요한 파라미터들은 근사적으로 추정한다. 제안한 방식을 통하여 잡음이 제거된 영상에 추가적으로 Wiener filter와 cycle-spinning을 적용하여 더 높은 PSNR (peak signal-to-noise ratio)값을 얻을 수 있다. 모의실험을 통해 제안한 방식의 PSNR 값과 결과영상으로 성능이 우수함을 확인하였다.

• The Journal of the Acoustical Society of Korea
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• v.35 no.3
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• pp.234-242
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• 2016

In this paper, an on-line noise coherence estimation algorithm for binaural speech enhancement system is proposed. A number of noise Power Spectral Density (PSD) estimation algorithms based on the noise coherence between two microphones have been proposed to improve the speech enhancement performance. In the conventional algorithms, the noise coherence was characterized using a real-valued analytic model. However, unlike the analytic model, the noise coherence between the two microphones is time-varying in real environments. Thus, in this paper, the noise coherence is updated in accordance with the variation of the acoustic environment to track the realistic noise coherence. The noise coherence can be updated only during the absence of speech, and the simulation results demonstrate the superiority of the proposed algorithm over the conventional algorithms based on the analytic model.

• Journal of the Korean Data and Information Science Society
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• v.20 no.5
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• pp.869-878
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• 2009

Image restoration techniques such as noise reduction and contrast enhancement have been researched for enhancing a contaminated image by the noise. An image degraded by additive random noise can be enhanced by noise reduction. Sigma filtering is one of the most widely used method to reduce the noise. In this paper, we propose a new sigma filter algorithm based on noise variance estimation which effectively enhances the degraded image by noise. Specifically, the Bartlett test is used to measure the degree of noise with respect to the degree of image feature. Simulation results are also given to show the performance of the proposed algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.230-235
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• 2005

In this paper, we propose an algorithm that improves a tone quality of a noisy audio signal in order to enhance a performance of perceptual filter using intelligent estimation of noise pattern from a band degraded by additive noise. The proposed method doesn't use the estimated noise which is obtained from silent range. Instead new estimated noise according to the power of signal and effect of noise variation is considered for each frame. So the noisy audio signal is enhanced by the method which controls a estimation of noise Pattern effectively in a noise corruption band. To show the performance of the proposed algorithm, various input signals which had a different signal-to-noise ratio(SNR) such as $5\cal{dB},\;10\cal{dB},\;15\cal{dB}\;and\;20\cal{dB}$ were used to test the proposed algorithm. we carry out SSNR and NMR of objective measurement and MOS test of subjective measurement. An approximate improvement of $7.4\cal{dB},\;6.8\cal{dB},\;5.7\cal{dB},\;5.1\cal{dB}$ in SSNR and $15.7\cal{dB},\;15.5\cal{dB},\;15.2\cal{dB},\;14.8\cal{dB}$ in NMR is achieved with the input signals, respectively. And we confirm the enhancement of tone quality in terms of mean opinion score(MOS) test which is result of subjective measurement.

• The Journal of the Acoustical Society of Korea
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• v.14 no.3
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• pp.90-96
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• 1995

A new method for autoregressive parameter estimation from noisy observation sequence is presented. This method, termed the AP method, is a result of an attempt to make use of the adaptive predictor which is a simple and reliable way of parameter estimation. It is shown theoretically that, for noisy input, the parameter vector computed from the prediction sequence is closer to that of the original sequence than the noisy input sequence is, under the spectral distortion criterion. Simulation results with the Kalman filter as a noise reduction filter and real speech data supported the theory. Roughly speaking, the performance of the parameter set obtained by the AP method is better than noisy one but worse than the EM iteration results. When the simplicity is considered, it could provide a useful alternative to more complicated parameter estimation methods in some applications.

• Journal of Advanced Navigation Technology
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• v.15 no.5
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• pp.735-741
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• 2011

In this paper, we have analyzed the effect of SNR estimation error on the BER performance of MMSE-DFE in high-speed binary CDMA system. Since MMSE equalization algorithm requires the SNR value of input signal, it should be estimated using CAZAC sequence in preamble. However, when AWGN and ISI exist simultaneously, it is impossible to estimate the exact SNR value of input signal and thereby equalizer's performance may be deteriorated. The simulation results can be used as a guideline for selection of SNR estimation algorithm for MMSE-DFE design.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.12 no.5
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• pp.519-526
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• 1987

An adaptive estimation system which operates propoerly in the environments corrupted by additive impulse noise in addition to the white Gaussian noise has been proposed. A feed forward loop is inserted into the adaptive estimator proposed by R. L. Moose for a system with an unknown measurement bias by which the improved adaptive estimator is processed successfully without the sum of the time varying weights being zero even when the measurement system is added impulue noise. Successfully processed adaptive estimator has been obtained under the large impulse noise in addition to randomly varying unknown biases condition by giving sufficient large value to the elements of discrete vector on the computer simulation.