• 제목/요약/키워드: weighted average algorithm

검색결과 137건 처리시간 0.025초

Virtual View Generation by a New Hole Filling Algorithm

  • Ko, Min Soo;Yoo, Jisang
    • Journal of Electrical Engineering and Technology
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    • 제9권3호
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    • pp.1023-1033
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    • 2014
  • In this paper, performance improved hole-filling algorithm which includes the boundary noise removing pre-process that can be used for an arbitrary virtual view synthesis has been proposed. Boundary noise occurs due to the boundary mismatch between depth and texture images during the 3D warping process and it usually causes unusual defects in a generated virtual view. Common-hole is impossible to recover by using only a given original view as a reference and most of the conventional algorithms generate unnatural views that include constrained parts of the texture. To remove the boundary noise, we first find occlusion regions and expand these regions to the common-hole region in the synthesized view. Then, we fill the common-hole using the spiral weighted average algorithm and the gradient searching algorithm. The spiral weighted average algorithm keeps the boundary of each object well by using depth information and the gradient searching algorithm preserves the details. We tried to combine strong points of both the spiral weighted average algorithm and the gradient searching algorithm. We also tried to reduce the flickering defect that exists around the filled common-hole region by using a probability mask. The experimental results show that the proposed algorithm performs much better than the conventional algorithms.

복원화소의 신뢰도 기반 가중 평균 필터를 활용한 Salt-and-Pepper 잡음 제거 알고리즘 (Noise Reduction Algorithm of Salt-and-Pepper Using Reliability-based Weighted Mean Filter)

  • 김동형
    • 디지털산업정보학회논문지
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    • 제17권2호
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    • pp.1-11
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    • 2021
  • Salt and pepper is a type of impulse noise. It may appear due to an error in the image transmission process and image storage memory. This noise changes the pixel value at any position in the image to 0 (in case of pepper noise) or 255 (in case of salt noise). In this paper, we present an algorithm for SAP noise reduction. The proposed method consists of three steps. In the first step, the location of the SAP noise is detected, and in the second step, the pixel value of the detected location is restored using a weighted average of the surrounding pixel values. In the last step, a reliability matrix around the reconstructed pixels is constructed, and additional correction is performed with a weighted average using this. As a result of the experiment, the proposed method appears to have similar or higher objective and subjective image quality than previous methods for almost all SAP noise ratios.

Distributed Uplink Resource Allocation in Multi-Cell Wireless Data Networks

  • Ko, Soo-Min;Kwon, Ho-Joong;Lee, Byeong-Gi
    • Journal of Communications and Networks
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    • 제12권5호
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    • pp.449-458
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    • 2010
  • In this paper, we present a distributed resource allocation algorithm for multi-cell uplink systems that increases the weighted sum of the average data rates over the entire network under the average transmit power constraint of each mobile station. For the distributed operation, we arrange each base station (BS) to allocate the resource such that its own utility gets maximized in a noncooperative way. We define the utility such that it incorporates both the weighted sum of the average rates in each cell and the induced interference to other cells, which helps to instigate implicit cooperation among the cells. Since the data rates of different cells are coupled through inter-cell interferences, the resource allocation taken by each BS evolves over iterations. We establish that the resource allocation converges to a unique fixed point under reasonable assumptions. We demonstrate through computer simulations that the proposed algorithm can improve the weighted sum of the average rates substantially without requiring any coordination among the base stations.

Weighted average of fuzzy numbers under TW(the weakest t-norm)-based fuzzy arithmetic operations

  • Hong, Dug-Hun;Kim, Kyung-Tae
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제7권1호
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    • pp.85-89
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    • 2007
  • Many authors considered the computational aspect of sup-min convolution when applied to weighted average operations. They used a computational algorithm based on a-cut representation of fuzzy sets, nonlinear programming implementation of the extension principle, and interval analysis. It is well known that $T_W$(the weakest t-norm)-based addition and multiplication preserve the shape of L-R type fuzzy numbers. In this paper, we consider the computational aspect of the extension principle by the use of $T_W$ when the principle is applied to fuzzy weighted average operations. We give the exact solution for the case where variables and coefficients are L-L fuzzy numbers without programming or the aid of computer resources.

Nearest-Neighbors Based Weighted Method for the BOVW Applied to Image Classification

  • Xu, Mengxi;Sun, Quansen;Lu, Yingshu;Shen, Chenming
    • Journal of Electrical Engineering and Technology
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    • 제10권4호
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    • pp.1877-1885
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    • 2015
  • This paper presents a new Nearest-Neighbors based weighted representation for images and weighted K-Nearest-Neighbors (WKNN) classifier to improve the precision of image classification using the Bag of Visual Words (BOVW) based models. Scale-invariant feature transform (SIFT) features are firstly extracted from images. Then, the K-means++ algorithm is adopted in place of the conventional K-means algorithm to generate a more effective visual dictionary. Furthermore, the histogram of visual words becomes more expressive by utilizing the proposed weighted vector quantization (WVQ). Finally, WKNN classifier is applied to enhance the properties of the classification task between images in which similar levels of background noise are present. Average precision and absolute change degree are calculated to assess the classification performance and the stability of K-means++ algorithm, respectively. Experimental results on three diverse datasets: Caltech-101, Caltech-256 and PASCAL VOC 2011 show that the proposed WVQ method and WKNN method further improve the performance of classification.

Design of 3D Laser Radar Based on Laser Triangulation

  • Yang, Yang;Zhang, Yuchen;Wang, Yuehai;Liu, Danian
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권5호
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    • pp.2414-2433
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    • 2019
  • The aim of this paper is to design a 3D laser radar prototype based on laser triangulation. The mathematical model of distance sensitivity is deduced; a pixel-distance conversion formula is discussed and used to complete 3D scanning. The center position extraction algorithm of the spot is proposed, and the error of the linear laser, camera distortion and installation are corrected by using the proposed weighted average algorithm. Finally, the three-dimensional analytic computational algorithm is given to transform the measured distance into point cloud data. The experimental results show that this 3D laser radar can accomplish the 3D object scanning and the environment 3D reconstruction task. In addition, the experiment result proves that the product of the camera focal length and the baseline length is the key factor to influence measurement accuracy.

Decentralized Moving Average Filtering with Uncertainties

  • Song, Il Young
    • 센서학회지
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    • 제25권6호
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    • pp.418-422
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    • 2016
  • A filtering algorithm based on the decentralized moving average Kalman filter with uncertainties is proposed in this paper. The proposed filtering algorithm presented combines the Kalman filter with the moving average strategy. A decentralized fusion algorithm with the weighted sum structure is applied to the local moving average Kalman filters (LMAKFs) of different window lengths. The proposed algorithm has a parallel structure and allows parallel processing of observations. Hence, it is more reliable than the centralized algorithm when some sensors become faulty. Moreover, the choice of the moving average strategy makes the proposed algorithm robust against linear discrete-time dynamic model uncertainties. The derivation of the error cross-covariances between the LMAKFs is the key idea of studied. The application of the proposed decentralized fusion filter to dynamic systems within a multisensor environment demonstrates its high accuracy and computational efficiency.

변형된 $\chi^2$- 테스트와 자동 임계치-결정 알고리즘을 이용한 장면전환 검출 기법 (A Scene Change Detection Technique using the Weighted $\chi^2$-test and the Automated Threshold-Decision Algorithm)

  • 고경철;이양원
    • 전자공학회논문지CI
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    • 제42권4호
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    • pp.51-58
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    • 2005
  • 본 논문에서는 비디오 시퀀스의 자동분류를 지원하기 위한 기반기술로서, 변형된 $\chi^2$-테스트와 자동 임계치-결정 알고리즘을 이용한 장면전환 검출 기법을 제안하였다. 변형된 $\chi^2$-테스트는 기존의 컬러 히스토그램에서 컬러의 각 채널공간(RGB)에 NTSC표준에 따른 명암도 등급을 따로 계산하여 채널의 차이 값을 보다 세분화 할 수 있으며, 인접한 두 프레임사이의 상대적인 컬러 값의 차이를 강조하는$\chi^2$- 테스트를 결합하여 보다 강건한 장면전환 곁출을 시도하고 있다. 자동 임계치-결정 알고리즘은 변형된 $\chi^2$-테스트를 통하여 획득된 인접한 프레임들 사이의 차이 값들을 이용한다. 먼저, 차이 값들에 대한 전체 평균값을 계산한 후, 이 평균값을 만족하는 차이 값들만을 이용하여 다시 평균값을 계산하며, 이러한 평균값의 연속적인 계산 및 누적을 통하여 분산된 차이 값들로부터 가장 최적의 중간 평균값을 취하여 임계치로 설정하는 방법이다. 실험결과 제안된 장면전환 검출 방법과 자동 임계치-결정 알고리즘은 기존의 접근방법보다 효과적이며, 그 우수성을 보여주었다.

칼만필터를 적용한 Adaptive EWMA관리도 (Adaptive Exponentially Weighted Moving Average Control Chart Using a Kalman Filter)

  • 김양호;정윤성;김광섭
    • 산업경영시스템학회지
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    • 제16권28호
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    • pp.93-101
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    • 1993
  • In this paper, two adaptive exponentially weighted moving avenge control chart schemes which available for real-time are proposed. The weighting coefficient is estimated using a recursive kalman filter algorithm. Simulated average run lengths indicate the proposed schemes are sensitive to process shifts And their performance is comparable to CUSUM control chart and customary EWMA control chart.

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대리모델을 사용한 축류송풍기 블레이드의 형상 최적화 (Shape Optimization of Axial Flow Fan Blade Using Surrogate Model)

  • 김진혁;최재호;김광응
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2008년도 추계학술대회B
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    • pp.2440-2443
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    • 2008
  • This paper presents a three dimensional shape optimization procedure for a low-speed axial flow fan blade with a weighted average surrogate model. Reynolds-averaged Navier-Stokes equations with shear stress transport turbulence model are discretized by finite volume approximations. Six variables from airfoil profile and lean are selected as design variables. 3D RANS solver is used to evaluate the objective functions of total pressure efficiency. Surrogate approximation models for optimization have been employed to find the optimal design of fan blade. A search algorithm is used to find the optimal design in the design space from the constructed surrogate models for the objective function. The total pressure efficiency is increased by 0.31% with the weighted average surrogate model.

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