• 제목/요약/키워드: Adaptive Smoothing

검색결과 146건 처리시간 0.027초

Adaptive Noise Reduction Algorithm for an Image Based on a Bayesian Method

  • Kim, Yeong-Hwa;Nam, Ji-Ho
    • Communications for Statistical Applications and Methods
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    • 제19권4호
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    • pp.619-628
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    • 2012
  • Noise reduction is an important issue in the field of image processing because image noise lowers the quality of the original pure image. The basic difficulty is that the noise and the signal are not easily distinguished. Simple smoothing is the most basic and important procedure to effectively remove the noise; however, the weakness is that the feature area is simultaneously blurred. In this research, we use ways to measure the degree of noise with respect to the degree of image features and propose a Bayesian noise reduction method based on MAP (maximum a posteriori). Simulation results show that the proposed adaptive noise reduction algorithm using Bayesian MAP provides good performance regardless of the level of noise variance.

독립변수의 차원감소에 의한 Polynomial Adaline의 성능개선 (Performance Improvement of Polynomial Adaline by Using Dimension Reduction of Independent Variables)

  • 조용현
    • 한국산업융합학회 논문집
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    • 제5권1호
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    • pp.33-38
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    • 2002
  • This paper proposes an efficient method for improving the performance of polynomial adaline using the dimension reduction of independent variables. The adaptive principal component analysis is applied for reducing the dimension by extracting efficiently the features of the given independent variables. It can be solved the problems due to high dimensional input data in the polynomial adaline that the principal component analysis converts input data into set of statistically independent features. The proposed polynomial adaline has been applied to classify the patterns. The simulation results shows that the proposed polynomial adaline has better performances of the classification for test patterns, in comparison with those using the conventional polynomial adaline. Also, it is affected less by the scope of the smoothing factor.

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콘크리트 압축강도 추정을 위한 적응적 확률신경망 기법 (Adaptive Probabilistic Neural Network for Prediction of Compressive Strength of Concrete)

  • 김두기;이종재;장성규
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 2004년도 가을 학술발표회 논문집
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    • pp.542-549
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    • 2004
  • The compressive strength of concrete is commonly used criterion in producing concrete. However, the tests on the compressive strength are complicated and time-consuming. More importantly, it is too late to make improvement even if the test result does not satisfy the required strength, since the test is usually performed at the 28th day after the placement of concrete at the construction site. Therefore, accurate and realistic strength estimation before the placement of concrete is being highly required. In this study, the estimation of the compressive strength of concrete was performed by probabilistic neural network (PNN) on the basis of concrete mix proportions. The estimation performance of PNN was improved by considering the correlation between input data and targeted output value. Adaptive probabilistic neural network (APNN) was proposed to automatically calculate the smoothing parameter in the conventional PNN by using the scheme of dynamic decay adjustment algorithm. The conventional PNN and APNN were applied to predict the compressive strength of concrete using actual test data of a concrete company. APNN showed better results than the conventional PNN in predicting the compressive strength of concrete.

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A Study on Individual Tap-Power Estimation for Improvement of Adaptive Equalizer Performance

  • Kim, Nam-Yong
    • Journal of electromagnetic engineering and science
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    • 제4권1호
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    • pp.23-29
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    • 2004
  • In this paper we analyze convergence constraints and time constant of IT-LMS algorithm and derive a method of making it's time constant independent of signal power by using input variance estimation. The method for estimating the input variance is to use a single-pole low-pass filter(LPF) with common smoothing parameter value, θ. The estimator is with narrow bandwidth for large θ but with wide bandwidth for small θ. This small θ gives long term average estimation(low frequency) of the fluctuating input variance well as short term variations (high frequency) of the input power. In our simulations of multipath communication channel equalization environments, the method with large θ has shown not as much improved convergence speed as the speed of the original IT-LMS algorithm. The proposed method with small θ=0.01 reach its minimum MSE in 100 samples whereas the IT-LMS converges in 200 samples. This shows the proposed, tap-power normalized IT-LMS algorithm can be applied more effectively to digital wireless communication systems.

기하학적 적응제어에 의한 엔드밀링머시인의 안내면 오차 규명 (Identification of guideway errors in the end milling machine using geometric adaptive control algorithm)

  • 정성종;이종원
    • 대한기계학회논문집
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    • 제12권1호
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    • pp.163-172
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    • 1988
  • 본 논문에서는 GAC방법을 이용하여 공작기계의 안내면오차를 수치제어 공작기계가 가지고 있는 가공조건의 조절 능력을 이용하여 가공오차를 보상제어 함으로써 규명(identification)할 수 있는 방법을 제시한다.

삼차원 소성가공 공정 시뮬레이션을 위한 지능형 사면체 요소망 자동생성 (AUTOMATED ADAPTIVE TETRAHEDRAL ELEMENT GENERATION FOR THREE-DIMENSIONAL METAL FORMING SIMULATION)

  • 이민철;전만수
    • 한국소성가공학회:학술대회논문집
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    • 한국소성가공학회 2005년도 춘계학술대회 논문집
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    • pp.203-208
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    • 2005
  • In this paper, an automated adaptive mesh generation scheme, based on an advancing-front-Delaunay method, is developed for finite element simulation of three dimensional bulk metal forming processes. During the simulation, the finite element mesh system is adaptively remeshed whenever the mesh is unacceptable. Several schemes are developed such as curvature compensation scheme to minimize volume loss, optimal smoothing scheme to improve element quality, etc. The presented approach is evaluated and applied to automatic forging simulation in order to demonstrate the effect of the developed schemes.

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영상 복원을 위한 MRF 기반 적응적 노이즈 탐지 알고리즘 (MRF-based Adaptive Noise Detection Algorithm for Image Restoration)

  • 응웬 뚜안 안;홍민철
    • 한국멀티미디어학회논문지
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    • 제16권12호
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    • pp.1368-1375
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    • 2013
  • 본 논문에서는 공간 적응적인 노이즈 검출 및 제거 방식에 대해 제안한다. 관측 영상 및 첨가 노이즈가 가우시안 분포 특성을 갖고 있다는 가정 하에 국부 통계 특성을 이용하여 노이즈 매개 변수들을 예측하며, 예측된 매개변수들은 1차 마르코프 랜덤 장과 연동하여 노이즈 검출 과정의 제약 조건을 설정하기 위해 사용된다. 더불어, 노이즈 검출 과정에서 설정된 제약 조건에 따라 제안된 가변 크기의 적응 저주파 통과 필터를 사용하여 적응적으로 복원 영상의 완화 정도를 제어하였다. 실험 결과를 통해 제안 방식의 효율성을 입증할 수 있었다.

대기시간을 이용한 적응형 멀티미디어 동기화 기법 (Adaptive Multimedia Synchronization Using Waiting Time)

  • 이기성;이근왕;이종찬;오해석
    • 한국정보처리학회논문지
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    • 제7권2S호
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    • pp.649-655
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    • 2000
  • Real-time application programs have constraints which need to be met between media-data. These constraints represents the delay time ad quality of service between media-data to be presented. In order to efficiently describe the delay time and quality of service, a new synchronization mechanism is needed. Proposed paper is a dynamic synchronization that minimized the effects of adaptive transmission delay time. That is, the method meets the requirements of synchronization between media-dat by handling dynamically the adaptive waiting time resulted from variations of delay time. In addition, the mechanism has interval adjustment using maximum delay jitter time. This paper decreases the data loss resulted from variation of delay time and from loss time of media-data by means of applying delay jitter in order to deal with synchronization interval adjustment. Plus, the mechanism adaptively manages the waiting time of smoothing buffer, which leads to minimize the gap from the variation of delay time. The proposed paper is suitable to the system which requires the guarantee of high quality of service and mechanism improves quality of services such as decrease of loss rate, increase of playout rate.

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Local Similarity based Document Layout Analysis using Improved ARLSA

  • Kim, Gwangbok;Kim, SooHyung;Na, InSeop
    • International Journal of Contents
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    • 제11권2호
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    • pp.15-19
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    • 2015
  • In this paper, we propose an efficient document layout analysis algorithm that includes table detection. Typical methods of document layout analysis use the height and gap between words or columns. To correspond to the various styles and sizes of documents, we propose an algorithm that uses the mean value of the distance transform representing thickness and compare with components in the local area. With this algorithm, we combine a table detection algorithm using the same feature as that of the text classifier. Table candidates, separators, and big components are isolated from the image using Connected Component Analysis (CCA) and distance transform. The key idea of text classification is that the characteristics of the text parallel components that have a similar thickness and height. In order to estimate local similarity, we detect a text region using an adaptive searching window size. An improved adaptive run-length smoothing algorithm (ARLSA) was proposed to create the proper boundary of a text zone and non-text zone. Results from experiments on the ICDAR2009 page segmentation competition test set and our dataset demonstrate the superiority of our dataset through f-measure comparison with other algorithms.

전압 변경 오버헤드를 고려한 전력 관리 알고리즘 (A Power-Aware Scheduling Algorithm with Voltage Transition Overhead)

  • 권혁성;안병철
    • 한국멀티미디어학회논문지
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    • 제11권5호
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    • pp.641-650
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    • 2008
  • 휴대 기기의 보급 확대에 따라 작은 배터리의 사용 시간 연장을 위해 배터리의 전력 관리 기법이 필요하다. 기존의 전력 관리 기법들은 전압 변경에 따른 오버헤드를 고려하지 않거나 부분적으로 고려하였다. 따라서 전압 변경 오버헤드는 개인용 멀티미디어 시스템의 실시간 태스크의 스케줄을 보장 못하는 경우가 발생할 수 있다. 본 논문은 전압 변경 오버헤드를 고려하면서 시스템의 이용률 정보를 바탕으로 사용 가능한 주파수의 개수와 연속된 주파수 사이의 간격을 조절하여 소비 전력을 줄이는 전력 관리 알고리즘을 제안한다. 본 알고리즘은 주파수 변경 회수를 줄여 기존의 CC RT-DVS 방법과 smoothing 방법에 비해 10에서 25%정도 소비 전력을 절감할 수 있다.

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