• Journal of Information Processing Systems
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• 제7권1호
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• pp.103-110
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• 2011

In this paper, an adaptive motion vector smoothing scheme based on weighted vector median filtering is proposed in order to eliminate the motion outliers more effectively for improving the quality of side information in frame-based distributed video coding. We use a simple motion vector outlier reliability measure for each block in a motion compensated interpolated frame and apply weighted vector median filtering only to the blocks with unreliable motion vectors. Simulation results show that the proposed adaptive motion vector smoothing algorithm improves the quality of the side information significantly while maintaining low complexity at the encoder in frame-based distributed video coding.

• 한국전자파학회논문지
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• 제16권7호
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• pp.740-745
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• 2005

본 논문은 GSM 시스템의 다경로 환경에서 선형 제약형 어레이 처리기를 이용하여 주종형 어레이 처리와 공간 유화 방법으로 원하는 신호를 추정하는 성능에 대하여 논한다. SINR과 BER 성능에서 주종형 어레이 처리방법과 공간유화 방법이 선형 제약형 어레이 처리방법보다 우수한 반면, 공간 유화 방법의 성능이 주종형 어레이 처리기 보다 더 나은 것으로 나타났다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2002년도 추계학술대회논문집
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• pp.699-704
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• 2002

A method using beamforming algorithm has been developed to measure oblique incidence reflection coefficients of sound absorption materials. MUSIC(Multiple Signal Classification) method detects the angles of incidence and reflection. By separating the incident and reflected waves using beamforming method, the reflection coefficient is calculated. Spatial smoothing technique is also used to reduce the coherence between the incident and reflected waves. The test materials were modeled as a locally reacting surface. Numerical and experiment results are performed to verify the acuracy of proposed method.

• Journal of the Korean Statistical Society
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• 제36권1호
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• pp.57-76
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• 2007

Kriging is a nonparametric regression method used in geostatistics for estimating curves and surfaces for spatial data. It may come as a surprise that the Kriging estimator, normally derived as the best linear unbiased estimator, is also the solution of a particular variational problem. Thus, Kriging estimators can also be interpreted as generalized smoothing splines where the roughness penalty is determined by the covariance function of a spatial process. We build off the early work by Silverman (1982, 1984) and the analysis by Cox (1983, 1984), Messer (1991), Messer and Goldstein (1993) and others and develop an equivalent kernel interpretation of geostatistical estimators. Given this connection we show how a given covariance function influences the bias and variance of the Kriging estimate as well as the mean squared prediction error. Some specific asymptotic results are given in one dimension for Matern covariances that have as their limit cubic smoothing splines.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1988년도 전기.전자공학 학술대회 논문집
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• pp.3-6
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• 1988

The UCERSS algorithm is an extended MUSIC which is used to estimate incident angles of multiple wide band signals. The purpose of this paper is to extend the UCERSS in order to estimate the direction of arrivals of multiple wide band signals in multipath environment. The modifications of the UCERSS result in the wide band spatial smoothing and the UNSS approaches. Computer simulation results indicate that the performances of the UNSS are superior to those of the UCERSS and the wide band spatial smoothing method.

• Journal of electromagnetic engineering and science
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• 제15권1호
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• pp.37-43
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• 2015

We implemented a real-time radar system for an unmanned ground vehicle designed to run on unpaved or bumpy roads. The system must be able to detect slow targets in a cluttered environment and cover wide angular sections with high resolution at the same time. The system consists of array antennas, preprocessors for digital beam forming, and digital signal processors for the detection process which uses sawtooth waveforms and high-resolution estimation, and is called forward/backward spatial smoothing beamspace multiple signal classification (FBSS BS-MUSIC). We show that the sawtooth waveforms enhance the angular estimation capability of FBSS BS-MUSIC in addition to their well-known advantages of removing the ambiguity of targets and detecting slow targets with improved velocity resolution.

• 한국정보통신학회논문지
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• 제7권8호
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• pp.1708-1713
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• 2003

본 논문에서는 비디오 패킷 손실을 위한 새로운 시간적 에러 은폐 기법을 제안한다. 각 손실 블록에 대한 에러 은폐는 시간적 움직임 보상을 바탕으로 보상된 블록과 주변 블록간의 경계에 대한 공간적 스무딩 동작에 의해 수행된다. 모의실험에서 제안된 기법은 기존의 기법들에 비해 약 2㏈의 화질 향상을 가져왔다.

• 한국소음진동공학회논문집
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• 제13권6호
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• pp.438-444
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• 2003

A method using beamforming algorithm has been developed to measure oblique incidence reflection coefficients of sound absorption materials. MUSIC(multiple signal classification) method detects the angles of incidence and reflection. By separating the incident and reflected waves using beamforming method, the reflection coefficient is calculated. Spatial smoothing technique Is also used to reduce the coherence between the incident and reflected waves. Numerical and experiment results are performed to verify the accuracy of proposed method.

• Spatial Information Research
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• 제2권2호
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• pp.189-196
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• 1994

적응성 평활화필터(Adaptive smoothing filter)는 화상 처리용 필터의 하나로 화소들간의 밝기(intensity)차이가 많이 나는 곳은 그대로 보존시켜주고 차이가 많이 나지 않는곳은 평균을 내주는 필터이다. 일반적으로 도시지역 지도에서의 영역구분은 한정된 갯수의 색깔로 구분되어있기때문에 컴퓨터로 기존의 지돌르 입력하여 전자지도를 구성할 경우 필요한 색은 몇 가지고 제한된다. 인간이 기존의 인쇄된 지도를 인식할 때는 어느 한 영역의 색이 한 가지로 같다고 느끼지만 자세히 그 지도를 들여다 보면 한 가지 영역도 한가지 색이 아니라 요동하고 있음을 알 수 있다. 컴퓨터가 지도를 인식할 때는 하나의 영역이라도 이러한 미묘한 색의 차이를 인식하기 때문에 인간처럼 한 가지 색으로 인식하지 못 하고 색의 요동이 있는 것으로 인식한다. 이 때 적응성 평활화 필터를 통과시켜주면 같은 영역내에서의 요동을 감소시켜 같은 색으로 만들어 줄 수 있다. 본 논문에서는 기존의 도시지역 지도를 컴퓨터로 입력한 화상을 색분해 한 뒤 적응성 평활화 필터를 적용하여 지도상의 도로, 주거 지역등의 정보 추출을 단색깔로 구분해 내기가 수월해짐을 고찰하였으며, 이러한 방법은 앞으로 GIS의 도시지역 데이타 베이스 구축에 그 활용성이 기대된다.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1997년도 춘계학술대회
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• pp.279-282
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• 1997

Bayesian reconstruction methods for emission computed tomography have been a topic of interest in recent years, partly because they allow for the introduction of prior information into the reconstruction problem. Early formulations incorporated priors that imposed simple spatial smoothness constraints on the underlying object using Gibbs priors in the form of four-nearest or eight-nearest neighbors. While these types of priors, known as "membrane" priors, are useful as stabilizers in otherwise unstable ML-EM reconstructions, more sophisticated prior models are needed to model underlying source distributions more accurately. In this work, we investigate whether the "thin plate" model has advantages over the simple Gibbs smoothing priors mentioned above. To test and compare quantitative performance of the reconstruction algorithms, we use Monte Carlo noise trials and calculate bias and variance images of reconstruction estimates. The conclusion is that the thin plate prior outperforms the membrane prior in terms of bias and variance.