• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.6
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• pp.58-64
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• 2009

Digital radiography (DR) images are corrupted by the additive noise, and also distorted by system impulse response. These unwanted phenomena are obstacles to obtain the desired image. To recover the original image, we applied multiscale Wiener filters in wavelet domain for DR images. The multiscale Wiener filter is first proposed by Chen for the restoration of fractal signals which are distorted by the system impulse response and additive noise. In this paper, we extended the multiscale Wiener filter to the two dimensional data. To compare the performance of ours with others, some simulations are given for a couple of wavelet filters with different wavelet levels, system impulse reponses and various noise power. When the addive noise powers are between 20-32 dB, the signal to noise ratio(SNR) of the proposed system is 0.5-2.0 dB better than that of the traditional Wiener filter method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.1
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• pp.164-171
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• 2008

Adaptive equalizers are inevitable schemes in digital communication systems for compensating the transmission channel distortion. Additionally, to obtain the required BER(Bit Error Rate), the adaptive algorithms appropriate to the mobile communication channels are required. In this paper, we propose the NPDFE (Noise-Predictive Decision Feedback Equalizer) for communication systems performance improvement in mobile communication channels. The performance of the proposed NPDFE with QPSK (Quadrature Phase Shift Keying) is simulated under AWGN (Additive White Gaussian Noise), Ricean fading, ETSI (European Telecommunications Standards Institute) fading, and Rayleigh fading channels. The equalizers used in simulations are a LE (Linear Equalizer), a DFE (Decision Feedback Equalizer), and a NPDFE. Moreover, the equalizer performance criterion of the QPSK is the BER.

• Journal of information and communication convergence engineering
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• v.1 no.3
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• pp.119-122
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• 2003

In this paper presents equations which describe an average weighted spectrum of errors and average block error probabilities for noncoherent frequency shift keying (NCFSK) used in D-branch maximal ratio combining (MRC) diversity in independent very slow nonselective Nakagami fading channels. The average is formed over the instantaneous receiver signal to noise ratio (SNR) after combining. the analysis is limited to additive Gaussian noise.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.11a
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• pp.119-121
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• 2019

부가적 백색 잡음 모델(additive white Gaussian noise, AWGN에서 학습된 깊은 신경만 (deep neural networks)을 이용한 잡음 제거기는 제거하려는 잡음이 AWGN인 경우에는 뛰어난 성능을 보이지만 실제 카메라 잡음에 대해서 잡음 제거를 시도하였을 때는 성능이 크게 저하된다. 본 논문은 U-Net 구조의 깊은 인공신경망 모델에 residual block을 결합함으로서 실제 카메라 영상에서 기존 알고리즘보다 뛰어난 성능을 지니는 신경망을 제안하다. 제안한 방법을 통해 Darmstadt Noise Dataset에서 PSNR과 SSIM 모두 CBDNet 대비 향상됨을 확인하였다.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.4
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• pp.380-385
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• 1990

This Paper presents a general algorithm for the parameter estimation of an antoregressive moving average process observed in additive white noise. The algorithm is based on the Gauss-Newton recursive prediction error method. For the parameter estimation, the output measurement is modelled as an innovation process using the spectral factorization, so that noise free RPE ARMA estimation can be used. Using apriori known properties leads to algorithm with smaller computation and better accuracy be the parsimony principle. Computer simulation examples show the effectiveness of the proposed algorithm.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1920-1923
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• 2002

This paper proposes an impulse response shortening algorithm applicable to decision feedback equalization of single carrier wideband signal. When he impulse response shortening methods for narrowband signaling are applied to single carrier wideband signals, they result in noise enhancement problem, significantly deterioriting the receiver performance. This problem can be alleviated by educing the eigenvalue spread ratio of the impulse response, which can be achieved by adding additive white noise with small variance to the impulse response of the channel. The performance of the proposed scheme is verified by computer simulation.

• Proceedings of the Acoustical Society of Korea Conference
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• 1985.10a
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• pp.87-94
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• 1985

In this paper, enhancement of speech corrupted by additive white or colored noise is stuided. The nuconstrained frequency-domain block least-mean-square (UFBLMS) adaptation algorithm and its frequency-weighted version are newly applied to speech enhancement. For enhancement of speech degraded by white noise, the performance of the UFBLMS algorithm is superior to the spectral subtraction method or Wiener filtering technique by more than 3 dB in segmented frequency-weighted signal-to-noise ratio(FWSNERSEG) when SNR of speech is in the range of 0 to 10 dB. As for enhancement of noisy speech corrupted by colored noise, the UFBLMS algorithm is superior to that of the spectral subtraction method by about 3 to 5 dB in FWSNRSEG. Also, it yields better performance by about 2 dB in FWSNR and FWSNRSEG than that of time-domain least-mean-square (TLMS) adaptive prediction filter(APF). In view of the computational complexity and performance improvement in speech quality and intelligibility, the frequency-weighted UFBLMS algorithm appears to yield the best performance among various algorithms in enhancing noisy speech corrupted by white or colored noise.

• Proceedings of the KSPS conference
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• 2002.11a
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• pp.179-182
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• 2002

The development of noise robust speech processing systems is becoming increasingly important as speech technology is currently widely applied in real world applications. Recently, to resolve such a noise problem, adaptive noise canceller(ANC) is frequently used, which is based upon adaptive filters. The adaptive recursive filters perform better than adaptive non-recursive filters due to the added poles, but the stability may be severely threatened. But these problems of adaptive recursive filters was solved by ACHARF algorithm. This paper presents a method which combines speaker verification system with ANC(Adaptive Noise Canceller) using the ACHARF algorithm. In the front-end stage, ANC is adopted to suppress the additive noise imposed on the speech signal. The results show that the performance of speaker verification system becomes better than before.

• Proceedings of the KSRS Conference
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• 2007.03a
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• pp.126-129
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• 2007

In this paper, an iterative MAP approach using a Bayesian model based on the lognormal distribution for image intensity and a GRF for image texture is proposed for despeckling the SAR images that are corrupted by multiplicative speckle noise. When the image intensity is logarithmically transformed, the speckle noise is approximately Gaussian additive noise, and it tends to a normal probability much faster than the intensity distribution. The MRF is incorporated into digital image analysis by viewing pixel type s as states of molecules in a lattice-like physical system defined on a GRF. Because of the MRFGRF equivalence, the assignment of an energy function to the physical system determines its Gibbs measure, which is used to model molecular mteractions. The proposed adaptive iterative method was evaluated using simulation data generated by the Monte Carlo method. In the extensive experiments of this study, the proposed method demonstrated the capability to relax speckle noise and estimate noise-free intensity.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.1
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• pp.85-95
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• 1995

The error intensity models for the ML estimation of a signal parameter have been developed in a companion paper [1]. While the methods described in [1] are applicable to any estimation problem with continuous parameters, our main application in this paper is the time delay estimation, and comparisons among the models derived in [1] (i.e. LC, LM, and ALM models)have been made. We first consider the case where only additive Gaussian noise is involved, and then the shot noise environment where coherent impulsive noise is also involved in addition to the Gaussian noise. We compare the models in terms of the probability of error, MSE(Mean Squared Error), and the computational complexity, which are the most important performance criteria in the analysis of parameter estimation. In conclusion, the ALM model turned out to be the most adequate model of all from the viewpoints of the criteria mentioned above.