• Journal of the Korean Institute of Telematics and Electronics T
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• v.35T no.2
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• pp.13-19
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• 1998

The Median of a set of number is a number which partitions the given set. The specified numbers of a set partitions in one subset and in another subset. In Image Processing, The Sorting method of numbers of one subset equal to the previous Median Filtering. but The Sorting method of numbers of another subset not equal to in the other. In this paper, a fast two-dimentional Median Filtering Algorithm is proposed. The Algorithm designed in such a during the partitioning of the previous window are used. Test results obtained by running the Algorithm on IBM PC(586) are presented and its filtering. It is shown that the proposed Algorithm's processing time is faster and independent of the number of bits used to represent the data values.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.1A
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• pp.43-47
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• 2000

In regions of low signal-to-noise ratio (SNR), performance analysis uses simulations of hybrid concatenated coding systems. However, for higher SNR regions beyond simulation capabilities, average upper bounds to bit error rate (BER) and word error rate (WER) are used. In [1], all weight enumerating functions are needed to obtain average bounds. In this paper, we use RSC as constituent codes, by using effective free distances instead of WEF, we derive average BER and WER bounds of hybrid concatenated convolutional codes (HCCC) and analyze the BER and WER over AWGN and Rayleigh/Rician fading channels.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.3
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• pp.613-620
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• 2010

Additive noise and channel distortion strongly degrade the performance of speaker verification systems, as it introduces distortion of the features of speech. This distortion causes a mismatch between the training and recognition conditions such that acoustic models trained with clean speech do not model noisy and channel distorted speech accurately. This paper presents a phase-related feature extraction method in order to improve the robustness of the speaker verification systems. The instantaneous frequency is computed from the phase of speech signals and features from the histogram of the instantaneous frequency are obtained. Experimental results show that the proposed technique offers significant improvements over the standard techniques in both clean and adverse testing environments.

• Journal of the Korea Society of Computer and Information
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• v.3 no.2
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• pp.139-146
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• 1998

This paper proposes a regularized iterative image restoration using method of conjugate gradient considering a priori information. Compared with conventional regularized method of conjugate gradient, this method has merits to prevent the artifacts by ringing effects and the partial magnification of the noise in the course of restoring the image degraded by blur and additive noise. Proposed method applies the constraints to accelerate the convergence ratio near the edge portions, and the regularized parameter suppresses the magnification of the noise. As experimental results, I show the superior convergence ratio and the suppression by the artifacts of the proposed method compared with conventional methods.

• The Journal of the Acoustical Society of Korea
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• v.18 no.8
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• pp.42-47
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• 1999

In this paper, a mixture interacting multiple model (MIMM) algorithm is proposed to enhance speech contaminated by additive nonstationary noise. In this approach, a mixture hidden filter model (HFM) is used to model the clean speech and the noise process is modeled by a single hidden filter. The MIMM algorithm, however. needs large computation time because it is a recursive method based on multiple Kalman filters with mixture HFM. Thereby, a computationally efficient implementation of the algorithm is developed by exploiting the structure of the Kalman filtering equation. The simulation results show that the proposed method offers performance gain compared to the previous results in [4,5] with slightly increased complexity.

• 한국지형공간정보학회:학술대회논문집
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• 1994.10a
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• pp.42-46
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• 1994

In this paper, we studied on an efficient detection and removal of the periodic scanner interference noise in LANDSAT images. Firstly, noise models and their characteristics are discussed. And we proposed a new scheme of noise detection in Fourier domain. Then, an dfficient noise filter can be designed based on the detected noise components. To verifythe effectiveness of our scheme, some experiments guided by our proposed scheme are performed using a real LANDSAT image.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2021.06a
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• pp.297-300
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• 2021

영상 잡음 제거는 잡음으로 저하된 영상으로부터 잡음 없는 영상을 복원하는 기술이다. 최근 영상 처리에 딥러닝을 사용한 학습 기반 방법 중 저수준 컴퓨터 비전 분야에 고수준 영상 정보를 활용하는 접근이 있었다. 본 논문에서는 고수준 영상 정보인 영상 분할 지도를 활용하여 영상 속 가산 백색 잡음 제거 연구를 진행하였다. 잔차 연결을 활용한 구조의 인공신경망 모델에 잡음 영상, 잡음 수준 지도, 영상 분할 지도를 입력으로 넣어 고수준 영상 정보를 활용할 수 있게 하였다. 본 논문에서 제안한 인공신경망을 Outdoor Scene Dataset과 CBSD68 Dataset에 대해 확인해본 결과, PSNR과 인지적인 측면에서 DnCNN과 FFDNet보다 성능이 향상되는 것을 확인하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.1
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• pp.14-24
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• 2017

In this paper, we propose a new EIM(erasure insertion method) based on the average-minimal-noise-power for HOM(higher order modulation) over AWGN(additive white Gaussian noise) under PBJ(partial-band jamming). Then we design SFH/SS(slow-frequency-hopping spread-spectrum) system by applying this method and formulate the PER(packet error rate) of the system. Based on this formula, we propose a new method to set the optimal threshold of the EIM and verify it at the designed 16-QAM SFH/SS system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.1
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• pp.155-160
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• 1996

In this paper, we consider the discrete-time known signal detection problem under the presence of additive noise exhibiting weak dependence. We derive the locally optimum, memoryless, and one-memory detector test statistics under a seakly dependent noise model. The performance characteristics of the one-memory detector can achieve almost optimum performance at the expense of only one memory unit under the weakly dependent noise model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.13 no.3
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• pp.270-276
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• 1988

The problem of detecting weak random signals is addressed in a generalized observation model incorporating multiplicative noised which has recently been introduced. It is shown that the locally optimum random-signal detectors in the multiplicative-noise model are interseting generalizations of those which would be obtained in the purely-additive noise model. Examples of explicits results for the locally optimum detector test statistics are given for two typical cases of well-known pdfs.