• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.3
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• pp.211-218
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• 2015

The analysis of remote sensing data depends on sensor specifications that provide accurate and consistent measurements. However, it is not easy to establish confidence and consistency in data that are analyzed by different sensors using various radiometric scales. For this reason, the cross-calibration method is used to calibrate remote sensing data with reference image data. In this study, we used an airborne hyperspectral image in order to calibrate a multispectral image. We presented an automatic cross-calibration method to calibrate a multispectral image using hyperspectral data and spectral mixture analysis. The spectral characteristics of the multispectral image were adjusted by linear regression analysis. Optimal endmember sets between two images were estimated by spectral mixture analysis for the linear regression analysis, and bands of hyperspectral image were aggregated based on the spectral response function of the two images. The results were evaluated by comparing the Root Mean Square Error (RMSE), the Spectral Angle Mapper (SAM), and average percentage differences. The results of this study showed that the proposed method corrected the spectral information in the multispectral data by using hyperspectral data, and its performance was similar to the manual cross-calibration. The proposed method demonstrated the possibility of automatic cross-calibration based on spectral mixture analysis.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.820-824
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• 2003

One of the most important research areas on remote sensing is spectral unmixing of hyper-spectral data. For spectral unmixing of hyper spectral data, accurate land cover information is necessary. But obtaining accurate land cover information is difficult process. Obtaining land cover information from high-resolution data may be a useful solution. In this study spectral signature of endmembers on ASTER acquired in October was calculated from land cover information on IKONOS acquired in September. Then the spectral signature of endmembers applied to ASTER images acquired on January and March. Then the result of spectral unmxing of them evauateted. The spectral signatures of endmembers could be applied to different seasonal images. When it applied to an ASTER image which have similar zenith angle to the image of the spectral signatures of endmembers, spectral unmixing result was reliable. Although test data has different zenith angle from the image of spectral signatures of endmembers, the spectral unmixing results of urban and vegetation were reliable.

• ETRI Journal
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• v.40 no.5
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• pp.634-642
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• 2018

Projection spectral analysis is investigated and refined in this paper, in order to unify principal component analysis and independent component analysis. Singular value decomposition and spectral theorems are applied to nonsymmetric correlation or covariance matrices with multiplicities or singularities, where projections and nilpotents are obtained. Therefore, the suggested approach not only utilizes a sum-product of orthogonal projection operators and real distinct eigenvalues for squared singular values, but also reduces the dimension of correlation or covariance if there are multiple zero eigenvalues. Moreover, incremental learning strategies of projection spectral analysis are also suggested to improve the performance.

• International Journal of Naval Architecture and Ocean Engineering
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• v.3 no.2
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• pp.116-121
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• 2011

The Spectral Fatigue Analysis is representative fatigue life assessment method for vessels. This Analysis is performed generally for the whole vessel and many assessment sites. The spectral fatigue analysis is performed through the process of hydrodynamic response analysis, global structural analysis, local structural analysis and calculation of fatigue damage. In these processes, fatigue damage is affected by many variables. The representative variables are S-N curve data, wave scatter data, wave spectrum, bandwidth effect and etc. In this paper, the effects of these variables to the fatigue damage are analyzed through the spectral fatigue analysis for 170k LNGC.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1654-1659
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• 2003

This paper introduces a fast Fourier transform (FFT)-based spectral analysis method for the transient responses as well as the steady-state responses of linear discrete systems. The force vibration of a viscously damped three-DOF system is considered as the illustrative numerical example. The proposed spectral analysis method is evaluated by comparing with the exact analytical solutions as well as with the numerical solutions obtained by the Runge-Kutta method.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.1
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• pp.9-12
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• 2006

A spectral analysis and numerical simulation are employed to assess the effects of the stylus tip radius on measuring surface profiles. Original profiles with fractal spectral densities are generated and then are numerically traced with circular tipped stylus. Instead of their spectral densities, the accumulative power spectrums of traced profiles are analyzed. It is shown that the minimum wavelength of traced profile relates directly to the radius r of the stylus tip and the root-mean-square (rms) roughness ${\sigma}_o$ of original profile. From this accumulation spectral analysis, a formula is developed to estimate the minimum wavelength of traced profile. By using the concept of the minimum wavelength, an appropriate stylus tip radius can be chosen for the given rms roughness ${\sigma}_o$ of the profile.

• Structural Engineering and Mechanics
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• v.71 no.3
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• pp.291-303
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• 2019

In the paper the analysis of natural vibrations of the transmission line with use of spectral elements and the laboratory experiments is performed. The purpose of the investigation is to analyze the natural vibrations of the transmission line and compare with the results obtained in the numerical simulations. Particular attention is paid to the hysteretic and aerodynamic damping analysis. Sensitivity of the wave number is performed for changing of the tension force, as well as for the different damping parameters. The numerical model is made using the Spectral Element Method. In the spectral model, for various parameters of stiffness, damping and tension force, the system response is checked and compared with the results of the accelerations obtained in the measurements. A frequency response functions (FRF) are calculated. The credibility of the model is assessed through a validation process carried out by comparing graphical plots of FRF and time history analysis and numerical values expressing differences in acceleration amplitude (MSG), phase angle differences (PSG) and differences in acceleration and phase angle total (CSG) values. The next aspect constituting the purpose of this paper is to present the wide possibilities of modelling and simulation of slender conductors using the Spectral Element Method. The obtained results show good accuracy in the range of both experimental measurements as well as simulation analysis. The paper emphasizes the ease with which the sensitivity of the conductor and its response to changes in density of spectral mesh division, tensile strength or material damping can be studied.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.789-794
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• 2007

Recently, the necessity of efficient and exact method to analyze structures is increasing with the importance of the seismic analysis. But the finite element method used in many field do not give the exact solution unless the length of the element is very short enough to represent the deformation of the element. Because the amount of computer calculation increase with the increasing of the number of degree of freedoms, the finite element method for the exact dynamic analysis of structures would not be efficient. To solve these problems, spectral clement method combined spectral method using the principle of wave mechanics and finite element method for the analysis of discrete models is applied to evaluate the behavior of the spatial structures. As a result of analysis. it becomes clear that the spectral element method is faster and more exact than the finite clement method.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.152-155
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• 2008

The blood flow characteristics have been closely related to various cardiovascular diseases, it is very important to predict them accurate enough in an efficient way. Thus, this paper proposes a one-dimensional spectral element model for the blood flow through blood vessels. The spectral element model is formulated by using the variational method. The nonlinear terms in spectral element model are all treated as the pseudo-force and an iterative solution method is applied in the frequency domain.

• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.1135-1143
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• 2007

The singular value decomposition and the spectral decomposition are the useful methods in the area of matrix computation for multivariate techniques such as principal component analysis and multidimensional scaling. These techniques aim to find a simpler geometric structure for the data points. The singular value decomposition and the spectral decomposition are the methods being used in these techniques for this purpose. In this paper, the singular value decomposition and the spectral decomposition are compared.