• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1362-1364
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• 2003

As non-isothermal mixed pixel is widely existed, the pixel-mean temperature cannot adequately represent the actual thermal state of land surface. The row crop was chosen as target to discuss the problem of component temperature retrieval. At first, the matrix model was found to express the thermal radiant directionality of the target. Then correlation of multi-angle infrared radiance was analyzed. In order to increase the retrieving accuracy, we chose the retrievable parameters and established the iterative method combining with inverse matrix to retrieve component temperature. It was proved by field experiment that the method could improve the retrieving accuracy and stability remarkably.

• Journal of the Optical Society of Korea
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• v.9 no.4
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• pp.157-161
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• 2005

Medical infrared imaging is obtained by measuring the self-emitted infrared radiance from the human body. Infrared emission is related to surface temperature and temperature is one of the most important physiological parameters related to health. Though recent applications such as security identification and oriental medicine have provided new fields of biomedical applications, infrared thermography has had ups and downs in its usages in cancer detection. Some of the main difficulties include finding proper applications and efficient diagnostic algorithms. In this study, infrared thermal imaging was used to detect regional metastasis of breast cancer. Our measurements were done for 110 women. From 63 individuals of a Healthy Group and a Benign Breast Disease Group, we developed algorithms for differentiating malignant regional metastasis based on temperature difference and asymmetry of temperature distribution. Testing with 47 cancer patients, we achieved a positive predictive value of $87.5\%$ and a negative predictive value of $95.6\%$. The results were better than for mammogram examination. A proper analysis of infrared imaging proved to be a highly informative and sensitive method for differentiating regional cancer metastasis from normal regions.

• Korean Journal of Remote Sensing
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• v.24 no.5
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• pp.417-425
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• 2008

An image-based atmospheric correction software ATC is implemented using MATLAB and SML (Spatial Modeler Language in ERDAS IMAGINE), and it was tested using Landsat TM/ETM+ data. This ATC has two main functional modules, which are composed of a semiautomatic type and an automatic type. The semi-automatic functional module includes the Julian day (JD), Earth-Sun distance (ESD), solar zenith angle (SZA) and path radiance (PR), which are programmed as individual small functions. For the automatic functional module, these parameters are computed by using the header file of Landsat TM/ETM+. Three atmospheric correction algorithms are included: The apparent reflectance model (AR), one-percent dark object subtraction technique (DOS), and cosine approximation model (COST). The ACT is efficient as well as easy to use in a system with MATLAB and SML.

• Korean Journal of Remote Sensing
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• v.7 no.2
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• pp.149-163
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• 1991

This paper discusses the capabilities of airborne remotely sensed data to detect and classify forest damades. In this work the AMS (Aircraft Multiband Scanner) was used to obtain digital imagery at 300m altitude for forest damage inventory in the Black Forest of Germany. MSS(Multispectral Scanner) digital numbers were converted to spectral emittance and radiance values in 8 spectral bands from the visible to the thermal infrared and submitted to a maximum-likelihood classification for : (1) tree species ; and. (2) damage classes. As expected, the resulted, the results of MSS data with high spatial resolution 0.75m$\times$0.75m enabled the detection and identification of single trees with different damages and were nearly equivalent to the truth information of ground checked data.

• Korean Journal of Remote Sensing
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• v.15 no.4
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• pp.321-327
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• 1999

As an example of many possible applications of OSMI data, we present a method to detect red tides. In Korean waters, red tides usually occur in the South Sea where the turbidity is usually high due to strong tidal mixing in the shallow sea. The conventional case 1 chlorophyll algorithm cannot be applied since it cannot distinguish chlorophyll from SS (suspended sediments). In October 1998, a red tide outbreak occurred off the coast of KunSan. We analyzed the SeaWiFS data of the outbreak. The standard SeaWiFS chlorophyll algorithm OC-2 was poor in identifying the red tides. However, comparison of spectra of normalized water-leaving radiance indicates that red tide pixels can be distinguished from sediment-laden pixels. Channel 443 and 555 were effective in showing the spectral characteristics. We suggest K490 algorithm as an example in summarizing the information of the spectra and thereby in distinguishing the red tide pixels. Further development is desirable.

• Journal of the Semiconductor & Display Technology
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• v.19 no.4
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• pp.1-5
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• 2020

By adapting black body leadflame and thin film type Green A filter, we successfully demonstrated night vision imaging system (NVIS) Green A compatible LED. Fabricated NVIS compatible LEDs show small form factor compared to that of commercialized NVIS compatible LED. Especially, NVIS radiance and chromaticity of MIL-STD-3009 specification can be satisfied simultaneously and easily by controlling the color temperature of the white LED as well as the concentration of the Green A dye and the thickness of the Green A filter. The optimal dye concentration of the NVIS Green A filter is expected to be about 1 wt%. The results of this study are expected to contribute to miniaturization, weight reduction and localization of avionic display and lighting devices.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.600-602
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• 2022

2차원 이미지 또는 영상을 통한 자세 추정의 경우, 영상 내에서 발생할 수 있는 탐지 오류, 피사체 잘림, 폐색(Occlusion) 등으로 인해 자세 추정 정확도가 감소할 수 있다. 본 논문에서는 4장 이상의 다양한 각도로 촬영한 이미지를 NeRF(Neural Radiance Fields)를 통해 이미지 합성(Image synthesis)을 진행하여 3차원 모델을 생성한다. 이후 DeepLabCut을 사용하여 관절 좌표와 골격(Skeleton)을 구축한다. 구축한 골격을 인공지능에 학습시킨 뒤 2차원 영상에서의 관절 좌표 인식, 골격 구축, 자세 추정을 진행한다. 2차원 영상 테스트 데이터를 통해, 3차원 모델을 사전 학습한 인공지능 모델과 기존 2차원 이미지를 사용하여 학습한 인공지능 모델의 자세 추정 정확도를 비교한다.

• Korean Journal of Remote Sensing
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• v.36 no.2_1
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• pp.155-165
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• 2020

In this present study, the sensitivity of O₄ Air Mass Factor (AMF) to Aerosol Peak Height (APH) has been investigated using radiative transfer model according to various parameters(wavelength (340 nm and 477 nm), aerosol type (smoke, dust, sulfate), aerosol optical depth (AOD), surface reflectance, solar zenith angle, and viewing zenith angle). In general, it was found that O₄ AMF at 477 nm is more sensitive to APH than that at 340 nm and is stably retrieved with low spectral fitting error in Differential Optical Absorption Spectroscopy (DOAS) analysis. In high AOD condition, sensitivity of O₄ AMF on APH tends to increase. O₄ AMF at 340 nm decreased with increasing solar zenith angle. This dependency isthought to be induced by the decrease in length of the light path where O₄ absorption occurs due to the shielding effect caused by Rayleigh and Mie scattering at high solar zenith angles above 40°. At 477 nm, as the solar zenith angle increased, multiple scattering caused by Rayleigh and Mie scattering partly leads to the increase of O₄ AMF in nonlinear function. Based on synthetic radiance, APHs have been retrieved using O₄ AMF. Additionally, the effect of AOD uncertainty on APH retrieval error has been investigated. Among three aerosol types, APH retrieval for sulfate type is found to have the largest APH retrieval error due to uncertainty of AOD. In the case of dust aerosol, it was found that the influence of AOD uncertainty is negligible. It indicates that aerosol types affect APH retrieval error since absorption scattering characteristics of each aerosol type are various.

• Korean Journal of Remote Sensing
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• v.26 no.2
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• pp.251-262
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• 2010

In order to provide quantitative control of the standard products of Geostationary Ocean Color Imager (GOCI), on-board radiometric correction, atmospheric correction, and bio-optical algorithm are obtained continuously by comprehensive and consistent calibration and validation procedures. The calibration/validation for radiometric, atmospheric, and bio-optical data of GOCI uses temperature, salinity, ocean optics, fluorescence, and turbidity data sets from buoy and platform systems, and periodic oceanic environmental data. For calibration and validation of GOCI, we compared radiometric data between in-situ measurement and HyperSAS data installed in the Ieodo ocean research station, and between HyperSAS and SeaWiFS radiance. HyperSAS data were slightly different in in-situ radiance and irradiance, but they did not have spectral shift in absorption bands. Although all radiance bands measured between HyperSAS and SeaWiFS had an average 25% error, the 11% absolute error was relatively lower when atmospheric correction bands were omitted. This error is related to the SeaWiFS standard atmospheric correction process. We have to consider and improve this error rate for calibration and validation of GOCI. A reference target site around Dokdo Island was used for studying calibration and validation of GOCI. In-situ ocean- and bio-optical data were collected during August and October, 2009. Reflectance spectra around Dokdo Island showed optical characteristic of Case-1 Water. Absorption spectra of chlorophyll, suspended matter, and dissolved organic matter also showed their spectral characteristics. MODIS Aqua-derived chlorophyll-a concentration was well correlated with in-situ fluorometer value, which installed in Dokdo buoy. As we strive to solv the problems of radiometric, atmospheric, and bio-optical correction, it is important to be able to progress and improve the future quality of calibration and validation of GOCI.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.19-25
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• 2019

The CleanSYS(Clean SYStem) is operated to monitor air pollutants emitted from specific industrial complexes in Korea. So the industrial complexes without the system are directly monitored by the control officers. For efficient monitoring, studies using various sensors have been conducted to monitor air pollutants emitted from industrial complex. In this study, hyperspectral sensors were used to model and verify the equations for estimating the concentration of $NO_2$(nitrogen dioxide) in air pollutants emitted. For development of the equations, spectral radiance were observed for $NO_2$ at various concentrations with different SZA(Solar Zenith Angle), VZA(Viewing Zenith Angle), and RAA(Relative Azimuth Angle). From the observed spectral radiance, the calculated value of the difference between the values of the specific wavelengths was taken as an absorption depth, and the equations were developed using the relationship between the depth and the $NO_2$ concentration. The spectral radiance mixed gas of $NO_2$ and $SO_2$(sulfur dioxide) was used to verify the equations. As a result, the $R^2$(coefficient of determination) and RMSE(Root Mean Square Error) were different from 0.71~0.88 and 72~23 ppm according to the form of the equation, and $R^2$ of the exponential form was the highest among the equations. Depending on the type of the equations, the accuracy of the estimated concentration with varying concentrations is not constant. However, if the equations are advanced in the future, hyperspectral sensors can be used to monitor the $NO_2$ emitted from the industrial complex.