• Journal of the Optical Society of Korea
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• v.13 no.2
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• pp.193-200
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• 2009

A compact imaging spectrometer (COMIS) is currently under development for use in the STSAT3 microsatellite. COMIS images the Earth's surface and atmosphere with ground sampling distances of ${\sim}30m$ in the $18{\sim}62$ spectral bands ($4.0{\sim}1.05{\mu}m$) for the nadir looking at an altitude of 700 km. COMIS has an imaging telescope and an imaging spectrometer box into which three electronics PCBs are embedded. These are designed into a single assembly with dimensions of 35(L) $\times$ 20(W) $\times$ 12(H) $cm^3$ and a mass of 4.3 kg. Optomechanical design efforts are focused on manufacturing ease, alignment, assembly, testing and improved robustness in space environments. Finite element analysis demonstrates that COMIS will survive in launch and space environments and perform the system modulation transfer function (MTF) in excess of 0.29 at the Nyquist frequency of the CCD detector (38.5 lines-per-mm).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.7
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• pp.3543-3557
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• 2017

Compression is a very important technique for remotely sensed hyperspectral images. The lossless compression based on the recursive least square (RLS), which eliminates hyperspectral images' redundancy using both spatial and spectral correlations, is an extremely powerful tool for this purpose, but the relatively high computational complexity limits its application to time-critical scenarios. In order to improve the computational efficiency of the algorithm, we optimize its serial version and develop a new parallel implementation on graphics processing units (GPUs). Namely, an optimized recursive least square based on optimal number of prediction bands is introduced firstly. Then we use this approach as a case study to illustrate the advantages and potential challenges of applying GPU parallel optimization principles to the considered problem. The proposed parallel method properly exploits the low-level architecture of GPUs and has been carried out using the compute unified device architecture (CUDA). The GPU parallel implementation is compared with the serial implementation on CPU. Experimental results indicate remarkable acceleration factors and real-time performance, while retaining exactly the same bit rate with regard to the serial version of the compressor.

• Journal of Forest and Environmental Science
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• v.24 no.3
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• pp.151-154
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• 2008

Dramatic price increases of fossil fuels and the economic development of emerging nations accelerates the transformation of forest lands into monocultures, e.g. for biofuel production. On this account, cost efficient methods to enable the monitoring of land resources has become a vital ambition. The application of remote sensing techniques has become an integral part of forest attribute estimation and mapping. The aim of this study was to evaluate the potentials of the kNN method by combining terrestrial with remotely sensed data for the development of a pixel-based monitoring system for the small scaled mosaic of different land use types of the off-reserve forests of the Goaso forest district in Ghana, West Africa. For this reason, occurrence and distribution of land use types like cocoa and non-timber forest resources, such as bamboo and raphia palms, were estimated, applying the kNN method to ASTER satellite data. Averaged overall accuracies, ranging from 79% for plantain, to 83% for oil palms, were found for single-attribute classifications, whereas a multi-attribute approach showed overall accuracies of up to 70%. Values of k between 3 and 6 seem appropriate for mapping bamboo. Optimisation of spectral bands improves results considerably.

• Transactions on Electrical and Electronic Materials
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• v.18 no.6
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• pp.364-369
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• 2017

Double molybdate $NaGd_{1-x}(MoO_4)_2:Ho^{3+}/Yb^{3+}$ phosphors with proper doping concentrations of $Ho^{3+}$ and $Yb^{3+}$ ($x=Ho^{3+}+Yb^{3+}$, $Ho^{3+}=0$ and 0.05, and $Yb^{3+}=0$, 0.35, 0.40, 0.45, and 0.50) were successfully synthesized using the microwave sol-gel method. Well-crystallized particles formed after heat-treatment at $800^{\circ}C$ for 16 h showed fine and homogeneous morphologies with particle sizes of $1{\sim}3{\mu}m$. The spectroscopic properties were examined using photoluminescence emission and Raman spectroscopy. Under excitation at 980 nm, the upconversion doped samples exhibited strong yellow emissions, from the combination of strong emission bands at 545 nm and 655 nm in the green and red spectral regions, respectively. The strong 545 nm emission band in the green region corresponded to the $^5S_2/^5F_4{\rightarrow}^5I_8$ transition in the $Ho^{3+}$ ions, while the strong 655 nm band in the red region appeared because of the $^5F_5{\rightarrow}^5I_8$ transition in the $Ho^{3+}$ ions. The pump power dependence and the Commission Internationale de L'Eclairage chromaticity of the upconversion emission intensity were evaluated in detail.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.6-10
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• 2007

Classification of hyperspectral images is challenging. A very high dimensional input space requires an exponentially large amount of data to adequately and reliably represent the classes in that space. In other words in order to obtain statistically reliable classification results, the number of necessary training samples increases exponentially as the number of spectral bands increases. However, in many situations, acquisition of the large number of training samples for these high-dimensional datasets may not be so easy. This problem can be overcome by using multiple classifiers. In this paper we compared the effectiveness of two approaches for creating multiple classifiers, feature selection and feature extraction. The methods are based on generating multiple feature subsets by running feature selection or feature extraction algorithm several times, each time for discrimination of one of the classes from the rest. A maximum likelihood classifier is applied on each of the obtained feature subsets and finally a combination scheme was used to combine the outputs of individual classifiers. Experimental results show the effectiveness of feature extraction algorithm for generating multiple classifiers.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.2
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• pp.53-63
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• 2016

Monitoring of cyanobacteria bloom in reservoir systems is important for water managers responsible of water supply system. Cyanobacteria affect the taste and smell of water and pose considerable filtration problems at water use places. Harmful cyanobacteria bloom in reservoir have significant economic impacts. We develop a new method for estimating the cyanobacteria bloom using Landsat TM and ETM+ data. Developed model was calibrated and cross-validated with existing in situ measurements from Daecheong Reservoir's Water Quality Monitoring Program and Algae Alarm System. Measurements data of three stations taken from 2004 to 2012 were matched with radiometrically converted reflectance data from the Landsat TM and ETM+ sensor. Stepwise multiple linear regression was used to select wavelengths in the Landsat TM and ETM+ bands 1, 2 and 4 that were most significant for predicting cyanobacteria cell number and bio-volume. Based on statistical analysis, the linear models were that included visible band ratios slightly outperformed single band models. The final monitoring models captured the extents of cyanobacteria blooms throughout the 2004-2012 study period. The results serve as an added broad area monitoring tool for water resource managers and present new insight into the initiation and propagation of cyanobacteria blooms in Daecheong reservoir.

• Korean Journal of Acupuncture
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• v.20 no.3
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• pp.9-27
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• 2003

Objectives : The aim of this study was to examine the effects of electro-acupuncture(EA) at the SP6(Sameumgyo)-GB39(Hyeonjong) on normal human EEG using power spectral analysis. Methods : EEG power spectrum exhibit site-specific and state-related differences in specific frequency bands. In this study, power spectrum was used as a measure of complexity(LAXTHA Co., KOREA). 30 channel EEG study was carried out in 20 subjects $(20\;males;\;age=21.4{\pm}0.5\;years)$. Results : In $\alpha$(alpha) band, the power values at F4 channels(p<0.05) during the SP6-GB39 acupoints treatment was significantly increased. But, the power values at Fz channel during the non-acupoint treatment was significantly decreased . In $\beta$(beta) band, the power values at Fz, FTC1, T3 channels(p<0.05) was significantly increased during the SP6-GB39 acupoints treatment. In $\delta$(delta) band, the power values at F4, C3, Cz, CP1, Pz channels(p<0.05) during SP6-GB39 acupoints treatment were significantly decreased.

• Bulletin of the Korean Chemical Society
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• v.35 no.10
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• pp.3035-3040
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• 2014

A new efficient catalytic method for aza/thia-Michael addition reactions of amines/thiols with higher product yields has been developed. Combining single-walled carbon nanotubes (SWCNT) with triethylammonium hydrogen phosphate (TEAP) ionic liquid (IL) can work as a catalyst. We utilized Raman spectroscopy to gain insight into the interactions between IL and SWCNT. The interactions between SWCNT with TEAP were confirmed by the increasing intensity ratios and spectral shift in wavelength of the Raman D and G bands of SWCNT. Further, the morphology of the resulting composite materials of TEAP and SWCNT was determined by using scanning electron microscopy (SEM). Higher product yield in reduced reaction time is the key advantage of using bucky gel as a catalyst for Michael reaction.

• Current Optics and Photonics
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• v.4 no.3
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• pp.210-220
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• 2020

Aiming at the problem that the Local Sparse Difference Index algorithm has low accuracy and low efficiency when detecting target anomalies in a hyperspectral image, this paper proposes a Weighted Collaborative Representation and Sparse Difference-Based Hyperspectral Anomaly Detection algorithm, to improve detection accuracy for a hyperspectral image. First, the band subspace is divided according to the band correlation coefficient, which avoids the situation in which there are multiple solutions of the sparse coefficient vector caused by too many bands. Then, the appropriate double-window model is selected, and the background dictionary constructed and weighted according to Euclidean distance, which reduces the influence of mixing anomalous components of the background on the solution of the sparse coefficient vector. Finally, the sparse coefficient vector is solved by the collaborative representation method, and the sparse difference index is calculated to complete the anomaly detection. To prove the effectiveness, the proposed algorithm is compared with the RX, LRX, and LSD algorithms in simulating and analyzing two AVIRIS hyperspectral images. The results show that the proposed algorithm has higher accuracy and a lower false-alarm rate, and yields better results.

• Journal of Astronomy and Space Sciences
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• v.23 no.1
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• pp.1-10
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• 2006

We report the photometric properties in BVR bands for the resolved bright supergiant stars in the dwarf galaxy Holmberg II. The color-magnitude diagrams and color-color diagram of 374 resolved stars indicate that the majority of the member stars are supergiant stars with a wide range of spectral type between B-K. A comparison with theoretical evolutionary tracks indicates that the supergiant stars in the observed field have progenitor masses between ${\sim}10M_{\bigodot}\;and\;20M_{\bigodot}$. The exponent of luminosity function in V is in good agreement with those of the Small and Large Magellanic Clouds.