• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.397-400
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• 2007

For mapping the distribution of heavy metals in the mining area, field spectroscopy and hyperspectral remote sensing were used in this study. Although heavy metals are spectrally featureless from the visible to the short wave infrared range, possible variations in spectral signal due to heavy metals bound onto minerals can be explained with the metal binding reaction onto the mineral surface. Variations in the spectral absorption shapes of lattice OH and oxygen on the mineral surface due to the combination of heavy metals were surveyed over the range from 420 to 2400 nm. Spectral parameters such as peak ratio and peak area were derived and statistically linked to metal concentration levels in the streambed samples collected from the dry stream channels. The spatial relationships between spectral parameters and concentrations of heavy metals were yielded as well. Based on the observation at a ground level for the relationship between spectral signal and metal concentration levels, the spectral parameters were classified in a hyperspectral image and the spatial distribution patterns of classified pixels were compared with the product of analysis at the ground level. The degree of similarity between ground dataset and image dataset was statistically validated. These techniques are expected to support assessment of dispersion of heavy metal contamination and decision on optimal sampling point.

• Journal of Biosystems Engineering
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• v.40 no.2
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• pp.153-158
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• 2015

Purpose: The research presented in this paper applied the chemometric analysis to the near-infrared spectral data from line-scanned hyperspectral images of beef and fish meals in animal feeds. The chemometric statistical models were developed to distinguish beef meals from fish ones. Methods: The meal samples of 40 fish meals and 15 beef meals were line-scanned to obtain hyperspectral images. The spectral data were retrieved from each of 3600 pixels in the Region of Interest (ROI) of every sample image. The wavebands spanning 969 nm to 1551 nm (across 176 spectral bands) were selected for chemometric analysis. The partial least squares regression (PLSR) and the principal component analysis (PCA) methods of the chemometric analysis were applied to the model development. The purpose of the models was to correctly classify as many beef pixels as possible while misclassified fish pixels in an acceptable amount. Results: The results showed that the success classification rates were 97.9% for beef samples and 99.4% for fish samples by the PLSR model, and 85.1% for beef samples and 88.2% for fish samples by the PCA model. Conclusion: The chemometric analysis-based PLSR and PCA models for the hyperspectral image analysis could differentiate beef meals from fish ones in animal feeds.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.3
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• pp.15-20
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• 2008

High-spatial resolution remote sensing satellites (IKONOS-2, QuickBird and KOMPSAT-2) have provided low-spatial resolution multispectral images and high-spatial resolution panchromatic images. Image fusion or Pan-sharpening is a very important in that it aims at using a satellite image with various applications such as visualization and feature extraction through combining images that have a different spectral and spatial resolution. Many image fusion algorithms are proposed, most methods could not preserve the spectral information of original multispectral image after image fusion. In order to solve this problem, modified induction technique which reduce the spectral distortion of fused image is developed. The spectral distortion is adjusted by the comparison between the spatially degraded pan-sharpened image and original multispectral image and our algorithm is evaluated by QuickBird satellite imagery. In the experiment, pan-sharpened image by various methods can reduce spectral distortion when our algorithm is applied to the fused images.

• Journal of The Korean Astronomical Society
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• v.41 no.2
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• pp.39-47
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• 2008

Spectral line profiles of filaments/prominences to be observed by the Fast Imaging Solar Spectrograph (FISS) are studied. The main spectral lines of interests are $H{\alpha}$, Ca II 8542, and Ca II K. FISS has a high spectral resolving power of $2{\times}10^5$, and supports simultaneous dual-band recording. This instrument will be installed at the 1.6m New Solar Telescope (NST) of Big Bear Solar Observatory, which has a high spatial resolution of 0.065" at 500nm. Adopting the cloud model of radiative transfer and using the model parameters inferred from pre-existing observations, we have simulated a set of spectral profiles of the lines that are emitted by a filament on the disk or a prominence at the limb. Taking into account the parameters of the instrument, we have estimated the photon count to be recorded by the CCD cameras, the signal-to-noise ratios, and so on. We have also found that FISS is suitable for the study of multi-velocity threads in filaments if the spectral profiles of Ca II lines are recorded together with $H{\alpha}$ lines.

• Korean Journal of Remote Sensing
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• v.21 no.3
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• pp.173-188
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• 2005

The present study aims to derive and compare narrow and broad bandwidths of ocean color sensor’s algorithms for the study of monitoring highly dynamic coastal oceanic environmental parameters using high-resolution imagery acquired from Multi-spectral Camera (MSC) on KOMPSAT-2. These algorithms are derived based on a large data set of remote sensing reflectances ($R_{rs}$) generated by using numerical model that relates $b_b/(a + b_b)$ to $R_{rs}$ as functions of inherent optical properties, such as absorption and backscattering coefficients of six water components including water, phytoplankton (chl), dissolved organic matter (DOM), suspended sediment (SS) concentration, heterotropic organism (he) and an unknown component, possibly represented by bubbles or other particulates unrelated to the first five components. The modeled $R_{rs}$ spectra appear to be consistent with in-situ spectra collected from Korean waters. As Kompsat-2 MSC has similar spectral characteristics with Landsat-5 Thematic Mapper (TM), the model generated $R_{rs}$ values at 2 ㎚ interval are converted to the equivalent remote sensing reflectances at MSC and TM bands. The empirical relationships between the spectral ratios of modeled $R_{rs}$ and chlorophyll concentrations are established in order to derive algorithms for both TM and MSC. Similarly, algorithms are obtained by relating a single band reflectance (band 2) to the suspended sediment concentrations. These algorithms derived by taking into account the narrow and broad spectral bandwidths are compared and assessed. Findings suggest that there was less difference between the broad and narrow band relationships, and the determination coefficient $(r^2)$ for log-transformed data [ N = 500] was interestingly found to be $(r^2)$ = 0.90 for both TM and MSC. Similarly, the determination coefficient for log-transformed data [ N = 500] was 0.93 and 0.92 for TM and MSC respectively. The algorithms presented here are expected to make significant contribution to the enhanced understanding of coastal oceanic environmental parameters using Multi-spectral Camera.

• 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 Korea Institute of Military Science and Technology
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• v.24 no.3
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• pp.264-271
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• 2021

Raman spectroscopy is an equipment that is widely used for classifying chemicals in chemical defense operations. However, the classification performance of Raman spectrum may deteriorate due to dark current noise, background noise, spectral shift by vibration of equipment, spectral shift by pressure change, etc. In this paper, we compare the classification accuracy of various machine learning algorithms including k-nearest neighbor, decision tree, linear discriminant analysis, linear support vector machine, nonlinear support vector machine, and convolutional neural network under noisy and spectral shifted conditions. Experimental results show that convolutional neural network maintains a high classification accuracy of over 95 % despite noise and spectral shift. This implies that convolutional neural network can be an ideal classification algorithm in a real combat situation where there is a lot of noise and spectral shift.

• Journal of the Korean Geosynthetics Society
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• v.20 no.4
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• pp.141-149
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• 2021

In this study, an laboratory experiment was performed for prediction technology of water content in the ground using hyperspectral information. And the spectral reflectance with a specific wavelength band was obtained according to the fine and water content. Through it, the spectral information was normalized with the spectral index of the existing literature, and the relationship with the fine and water contents and the reliability of the prediction technology were analyzed. As a result of analysis, the spectral reflectance is decreased when the water and fine contents are increased under the high water contents. In addition, the reliability of prediction technology of water content was evaluated by examining 7 different spectral index calculation methods. Among them, DVI showed relatively high prediction reliability and was superior to other calculation methods in terms of sensitivity.

• Journal of the Korean Geosynthetics Society
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• v.21 no.4
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• pp.93-100
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• 2022

This study describes the evaluation results on the effect of soil particle surfaces coated with various hydrophobic conditions on spectral information according to water content. Wettability test and spectral information evaluation test were performed on the hydrophobic coated standard sand. When the standard sand was coated with 1%, 3%, and 5% hydrophobic, the contact angles of sand-water interface were 130°~143°, 129°~144°, and 131°~144°, respectively. This means that the contact angle increased as the degree of hydrophobic coating increased at the same drying time, but the range of the contact angle had the same wettability. This means that the contact angle increases as the hydrophobic coating degree increases at the same drying time, whereas the contact angle range has the same wettability. As a result of spectral information evaluation, the maximum spectral reflectance of the dried sand with hydrophobic condition decreased compared to that of the hydrophilic sand, as the degree of hydrophobic increased. However, the maximum spectral reflectance was increased by increasing the degree of hydrophobic under the same water content conditions.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.4
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• pp.392-400
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• 2001

This paper proposes an illuminant estimation algorithm that estimates the spectral power distribution of an incident light source from a single image. The proposed illumination recovery procedure has two phases. First, the surface spectral reflectances are recovered in the maximum achromatic region (MAR) which is the most achromatic and highly bright region of an image after removing partially the effect of illumination using a modified gray world algorithm. Here, the surface reflectances of MAR are estimated using the principal component analysis method along with a set of given 1269 Munsell samples. Second, the Population of reflected lights is determined with 1269 Munsell samples and a set of illuminations then the spectral distribution of re(looted lights of MAR is selected from the spectral database. That is, color differences are compared between the reflected lights of the MAR and the spectral database, which is the set of reflected lights built by the given set of Munsell samples and illuminants. Then the closest colors from the spectral database are selected. Finally, the illuminant of an image can be calculated dividing the average spectral distributions of reflected lights of MAR by the average surface reflectances of the MAR. In order to evaluate the proposed algorithm, experiments with artificial scenes, which are exposed to chromatic illuminants, were performed and the spectral distribution of estimated illumination and color difference are compared with results of the conventional method.