• Current Optics and Photonics
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• 제7권6호
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• pp.701-707
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• 2023

In laser imaging, accurate extraction of the laser's center is essential. Several methods exist to extract the laser's center in an image, such as the geometric mean, the parabolic curve fitting, and the Gaussian curve fitting, etc. The Gaussian curve fitting is the most suitable because it is based on the physical properties of the laser. The width of the Gaussian laser beam depends on the distance from the laser source to the target object. It is assumed in general that the distance remains constant at a laser spot resulting in a symmetric Gaussian model for the laser image. However, on a curved surface of the object, the distance is not constant; The laser beam is narrower on the side closer to the focal point of the laser light and wider on the side closer to the laser source, which causes the distribution of the laser beam to skew. This study presents a modified Gaussian model in the laser imaging to incorporate the slant angle of a curved object. The proposed method is verified with simulation and experiments.

• 한국정보통신학회논문지
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• 제8권7호
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• pp.1393-1398
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• 2004

영상은 획득, 저장 그리고 전송 등의 처리과정에서 다양한 원인에 의해 훼손되며, 이러한 영상을 복원하기 위한 많은 연구가 이루어지고 있다. 일반적으로 AWGN(additive white gaussian noise)에 의해 훼손된 영상을 복원하는 방법으로 평균 필터와 위너 필터가 있으며, 특히 평탄한 영역에서의 노이즈 제거에 평균 필터가 우수하다. 그러나 평균 필터는 영상의 특징을 고려하지 않으므로 에지 성분이 왜곡되어 평활화되는 단점이 있다. 따라서 본 논문에서는 평균 필터와 함께 에지 성분을 보존하면서 대조도 개선에 강한 위너 필터를 사용하여 각각 필터링한 후, 처리된 영상에 가중치를 설정하여 병렬처리하는 영상 복원 방법을 제안하였다.

• 대한전기학회논문지
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• 제40권9호
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• pp.929-936
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• 1991

An estimator for a discrete nonlinear system is derived in the sense of minimum mean square error. An optimal estimator for nonlinear system is very difficult to find and it will be infinite dimensional even if it is found. It has been known that the statistical linearization technique makes it possible to obtain a finite dimensional estimator. In this paper, the procedure of its derivation using the statistical linearization technique that gives an exact mean and variance information is introduced in the sense of minimum mean square error. The derived estimator cannot be clainmed to be globally optimal estimator because it uses the Gaussian assumption to the non-Gaussian distributed nonlinear output. However, the proposed filter exhibits a better performance compared to extended Kalman filter. Simulation results of a simple example present the improvement of the proposed filter in convergent property over the extended Kalman filter.

• 한국소음진동공학회논문집
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• 제12권8호
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• pp.616-625
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• 2002

In this paper, we drove the filtered-x least mean fourth (FXLMF) algorithm where the error raised to the power of four is minimized and analyzed its convergence behavior for a multiple sinusoidal acoustic noise and Gaussian measurement noise. The application of the FXLMF adaptive filter to active noise control requires to estimate the transfer characteristics of the acoustic path between the output and the error signal of the adaptive controller. The results of the convergence analysis of the FXLMF algorithm indicate that the effects of the parameter estimation inaccuracy on the convergence behavior of the algorithm are characterized by two distinct components phase estimation error and estimated gain. In particular, the convergence is shown to be strongly affected by the accuracy of the phase response estimate. Also, we newly show that the convergence behavior can differ depending on the relative sizes of the Gaussian noise and the convergence constant.

• 방송공학회논문지
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• 제22권5호
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• pp.608-617
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• 2017

영역 분리에 의한 명암대비 방법들이 제안되어 왔지만 영상의 히스토그램에 따라 과포화 되는 부작용이나 밝기 값 보존과 명암대비 효과의 상반 관계에 대한 개선이 필요하다. 본 논문은 다양한 히스토그램에서도 명암 대비가 개선 되도록 영역 분리 시 각 서브 영역이 가우시안 분포를 갖도록 분리하고 영역별 평활화하는 명암 대비 방법을 제안 한다. 영역 분리는 $L^*a^*b^*$ 컬러 공간에서 K-평균 방법과 기대-최대 방법에 의해 영역맵과 확률맵을 생성하며 영역별 히스토그램 평활화 방법은 영역간 히스토그램 중복 최소를 위해 평균값 이동과 영역 분리에서 생성된 확률맵을 변환 함수에 활용함으로써 영역별 밝기값을 보존 하였다. 실험은 기존의 명암 대비 방법들과 평균 밝기 차이와 평균 엔트로피 값을 이용하여 밝기 변화가 적고 영상의 세부 정보가 표현됨에 의한 명암대비 개선을 보인다.

• 한국정보과학회논문지:정보통신
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• 제29권5호
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• pp.553-561
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• 2002

이 논문에서는 자원을 공유하는 여러 개의 QoS(Quality of Service) 큐(queue)를 서비스하기 위한 새로운 서비스 규칙 - 선형 서비스 규칙을 제안하고, 그 특징을 분석하였다. 제안하는 선형 서버는 각각의 큐에 대한 출력 트래픽(traffic) 및 고객 수 과정을 입력 트래픽의 선형 함수로 만든다 특히 입력 트래픽이 가우스 분포를 갖는 경우에는 큐 길이의 분포와 출력 트래픽 분포가 모두 가우스 분포를 갖게 하며, 그 분포의 평균과 분산이 입력 트래픽의 평균과 전력 스펙트럼(power Spectrum)의 함수로 나타나게 한다. 중요한 QoS 척도인 버퍼 넘침 확률 및 지연 분포 역시 입력 트래픽의 평균과 전력 스펙트럼의 함수로 나타나게 된다. 이 연구는 네트워크의 각 노드를 하나의 선형 필터로 볼 수 있게 하므로, 선형 시스템 이론에 기초한 네트워크 전반에 걸친 트래픽 관리 기술의 새로운 방향을 제시하였다.

• Wind and Structures
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• 제35권6호
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• pp.419-430
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• 2022

In wind-resistant designs, wind velocity is assumed to be a Gaussian process; however, local complex topography may result in strong non-Gaussian wind features. This study investigates the non-Gaussian wind features over complex terrain under atmospheric turbulent boundary layers by the large eddy simulation (LES) model, and the turbulent inlet of LES is generated by the consistent discretizing random flow generation (CDRFG) method. The performance of LES is validated by two different complex terrains in Changsha and Mianyang, China, and the results are compared with wind tunnel tests and onsite measurements, respectively. Furthermore, the non-Gaussian parameters, such as skewness, kurtosis, probability curves, and gust factors, are analyzed in-depth. The results show that the LES method is in good agreement with both mean and turbulent wind fields from wind tunnel tests and onsite measurements. Wind fields in complex terrain mostly exhibit a left-skewed Gaussian process, and it changes from a softening Gaussian process to a hardening Gaussian process as the height increases. A reduction in the gust factors of about 2.0%-15.0% can be found by taking into account the non-Gaussian features, except for a 4.4% increase near the ground in steep terrain. This study can provide a reference for the assessment of extreme wind loads on structures in complex terrain.

• Communications for Statistical Applications and Methods
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• 제27권1호
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• pp.97-108
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• 2020

This paper compares several methods for estimating parameters of normal inverse Gaussian distribution. Ordinary maximum likelihood estimation and the method of moment estimation often do not work properly due to restrictions on parameters. We examine the performance of adjusted estimation methods along with the ordinary maximum likelihood estimation and the method of moment estimation by simulation and real data application. We also see the effect of the initial value in estimation methods. The simulation results show that the ordinary maximum likelihood estimator is significantly affected by the initial value; in addition, the adjusted estimators have smaller root mean square error than ordinary estimators as well as less impact on the initial value. With real datasets, we obtain similar results to what we see in simulation studies. Based on the results of simulation and real data application, we suggest using adjusted maximum likelihood estimates with adjusted method of moment estimates as initial values to estimate the parameters of normal inverse Gaussian distribution.

• 대한방사선기술학회지:방사선기술과학
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• 제22권2호
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• pp.53-56
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• 1999

A Gaussian distribution was parametrized for the initial distribution of the electron beam emitted from a 6MeV medical linear accelerator. A percent depth dose was measured in a water phantom and the corresponding Monte Carlo calculations were performed starting from a Gaussian distribution for a range of standard deviations, ${\sigma}=0.1$, 0.15, 0.2, 0.25, and 0.3 with being the mean value for the Incident beam energy. When measurement and calculation were compared, the calculation with the Gaussian distribution for ${\sigma}=0.25$ turned out to agree best with the measurement. The results from the present work can be utilized as input energy data in planning an electron beam therapy with a Monte Carlo calculation.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2011년도 추계학술대회
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• pp.379-381
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• 2011

The image signal is often affected by the existence of noise, noise can occur during image capture, transmission or processing phases. noises caused the degradation phenomenon and demage the original signal information. Many studies are being accomplished to restore those signals which corrupted by mixed noise. In this paper, we proposed mixed weighted filter for removing Gaussian and impulse noise. we first charge the noise type, then, Gaussian is removed by a weighted mean filter and impulse noise is removed by self-adaptive weighted median filter that can not only remove mixed noise but also preserve the details. And through the simulation, we compared with the conventional algorithms and indicated that proposed method significant improvement over many other existing algorithms and can preserve image details efficiently.