• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.6
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• pp.111-116
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• 2021

The hyper-spectral image is data obtained by dividing the electromagnetic wave band in the infrared region into hundreds of wavelengths. It is used to find or classify objects in various fields. Recently, deep learning classification method has been attracting attention. In order to use hyper-spectral image data as deep learning training data, a processing technique is required compared to conventional visible light image data. To solve this problem, we developed a software that selects specific wavelength images from the hyper-spectral data cube and performs the ground truth task. We also developed software to manage data including environmental information. This paper describes the configuration and function of the software.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.2
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• pp.46.1-46.1
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• 2018

The Fast Imaging Solar Spectrograph (FISS) on the Goode Solar Telescope (GST) at Big Bear Solar Observatory is the imaging Echelle spectrograph developed by the Solar Astronomy Group of Seoul National University and the Solar and Space Weather Group of Korea Astronomy and Space Science Institute. The instrument takes spectral data from a region on the Sun in two spectral bands simultaneously. The imaging is done by the organization of intensity data obtained from the fast raster scan of the slit over the field of view. Since the scan repeats many times, the whole set of data can be used to construct the movies of monochromatic intensity at arbitrary wavelengths within the spectral bands, and those of line-of-sight velocity inferred from different spectral lines. So far there are two standard observing configurations: one recording the $H{\alpha}$ line and the Ca II 8542 line simultaneously, and the other recording the Na I D2 line and Fe I 5435 line simultaneously. We have developed the procedures to produce the standard data for each observing configuration. The procedures include the spatial alignment, the correction of spectral shift of instrumental origin, and the lambdameter measurement of the line wavelength. The standard data include the movie of continuum intensity, the movies of intensity and velocity inferred from a chromospheric spectral line, the movies of intensity and velocity inferred from a photospheric line. The processed standard data will be freely available online (fiss.snu.ac.kr) to be used for research and public outreach. Moreover, the IDL procedures will be provided on request as well so that each researcher can adapt the programs for their own research.

• Journal of the Korean Mathematical Society
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• v.33 no.4
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• pp.717-734
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• 1996

For a scalar rational function, the spectral data consisting of zeros and poles with their respective multiplicities uniquely determines the function up to a nonzero multiplicative factor. But due to the richness of the spectral structure of a rational matrix function, reconstruction of a rational matrix function from a given spectral data is not that simple.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.36T no.1
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• pp.32-40
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• 1999

The analysis of logic function is performed by the spectral coefficients which transform the function domain data into the spectral domain data. By using the spectral techniques, analysis of MVL circuits is performaed, and the fault analysis and detecting methods of multiple-valued logic circuits are proposed in this paper.

• Journal of the Korean Mathematical Society
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• v.46 no.6
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• pp.1243-1254
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• 2009

The inverse scattering problem is investigated for some second order differential equation with a nonlinear spectral parameter in the boundary condition on the half line [0, $\infty$). In the present paper the coefficient of spectral parameter is not a pure imaginary number and the boundary value problem is not selfadjoint. We define the scattering data of the problem, derive the main integral equation and show that the potential is uniquely recovered.

• Journal of applied mathematics & informatics
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• v.22 no.1_2
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• pp.209-222
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• 2006

Estimation of the spectral measure, covariance and spectral density functions of a strictly stationary r-vector valued time series is considered, under the assumption that some of the observations are missed. The modified periodograms are calculated using data window. The asymptotic normality is studied.

• Communications of the Korean Mathematical Society
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• v.34 no.3
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• pp.1005-1014
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• 2019

A new simple method is proposed for reconstructing phylogenetic trees, which we call the spectral method. The most common distance based method is the neighbor-joining method which is based on the minimum evolution principle. The spectral method shows similar performance to the neighbor-joining method for simulated data generated by seq-gen. For real data, the spectral method shows much better performance than the neighbor-joining method. Hence it can be a complementary method for reconstructing phylogenetic trees.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.134-137
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• 2005

Unsupervised spectral angle classification (USAC) is the algorithm that can extract ground object information with the minimum 'Spectral Angle' operation on behalf of 'Spectral Euclidian Distance' in the clustering process. In this study, our algorithm uses the unit vector instead of the spectral distance to compute the mean of cluster in the unsupervised classification. The proposed algorithm (MUSAC) is applied to the Hyperion and ETM+ data and the results are compared with K-Meails and former USAC algorithm (FUSAC). USAC is capable of clearly classifying water and dark forest area and produces more accurate results than K-Means. Atmospheric correction for more accurate results was adapted on the Hyperion data (Hyperion-FLAASH) but the results did not have any effect on the accuracy. Thus we anticipate that the 'Spectral Angle' can be one of the most accurate classifiers of not only multispectral images but also hyperspectral images. Furthermore the cluster unit vector can be an efficient technique for determination of each cluster mean in the USAC.

• Journal of the Optical Society of Korea
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• v.12 no.4
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• pp.281-287
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• 2008

An acousto-optic tunable filter based 3-D micro surface profile measurement using an equally spaced 5 spectral phase shifting is described. The 5-bucket spectral phase shifting method is compared with a Fourier-transform method in the spectral domain. It can provide a fast measurement capability while maintaining high accuracy since it needs only 5 pieces of spectrally phase shifted imaging data and a simple calculation in comparison with the Fourier transform method that requires full wavelength scanning data and relatively complicated computation. The 3-D profile data of micro objects can be obtained in a few seconds with an accuracy of ${\sim}10nm$. The 3-D profile method also has an inherent benefit in terms of being speckle-free in measuring diffuse micro objects by employing an incoherent light source. Those simplicity and practical applicability is expected to have diverse applications in 3-D micro profilometry such as semiconductors and micro-biology.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.4
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• pp.400-407
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• 2011

Modeling and analysis of high-dimensional spectral data provide an opportunity to uncover inherent patterns in various information-rich data. Orthogonal signal correction (OSC) a preprocessing technique has been widely used to remove unwanted variations of spectral data that do not contribute to prediction or classification. In the present study we propose a novel OSC algorithm called adjusted direct OSC to improve visualization and the ability of classification. Experimental results with real mass spectral data from condom lubricants demonstrate the effectiveness of the proposed approach.