• Title/Summary/Keyword: weighted average algorithm

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Virtual View Generation by a New Hole Filling Algorithm

  • Ko, Min Soo;Yoo, Jisang
    • Journal of Electrical Engineering and Technology
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    • v.9 no.3
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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.

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

  • Kim, Donghyung
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.17 no.2
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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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    • v.12 no.5
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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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    • v.7 no.1
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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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    • v.10 no.4
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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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    • v.13 no.5
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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
    • Journal of Sensor Science and Technology
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    • v.25 no.6
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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.

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

  • Ko, Kyong-Cheol;Rhee, Yang-Won
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.42 no.4 s.304
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    • pp.51-58
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    • 2005
  • This paper proposes a robust scene change detection technique that uses the weighted chi-square test and the automated threshold-decision algorithms. The weighted chi-square test can subdivide the difference values of individual color channels by calculating the color intensities according to NTSC standard, and it can detect the scene change by joining the weighted color intensities to the predefined chi-square test which emphasize the comparative color difference values. The automated threshold-decision at algorithm uses the difference values of frame-to-frame that was obtained by the weighted chi-square test. At first, The Average of total difference values is calculated and then, another average value is calculated using the previous average value from the difference values, finally the most appropriate mid-average value is searched and considered the threshold value. Experimental results show that the proposed algorithms are effective and outperform the previous approaches.

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

  • 김양호;정윤성;김광섭
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.16 no.28
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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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Shape Optimization of Axial Flow Fan Blade Using Surrogate Model (대리모델을 사용한 축류송풍기 블레이드의 형상 최적화)

  • Kim, Jin-Hyuk;Choi, Jae-Ho;Kim, Kwang-Yong
    • Proceedings of the KSME Conference
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    • 2008.11b
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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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