• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.518-521
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• 2007

To retrieve Sea Surface Temperature(SST) from NOAA-AVHRR imagery the spilt window atmospheric correction algorithm is generally used. Recently, there have been various new algorithms developed to process these data, namely the variable-coefficient split-window, the R54 transmittance-ratio method, fixed-coefficient nonlinear algorithm, dynamic water vapour (DWV) correction method, Dynamic Water Vapour and Temperature algorithm (DWVT). We used MCSST (Multi-Channel Sea surface temperature) and NLSST(Non linear sea surface temperature) algorithms in this study. The study area is around the Korea sea area (Yellow Sea). We compared and analyzed with various methods by applying each Ocean in-situ data and satellite data. The primary aim of study is to verify and optimize algorithms. Finally, this study proposes an optimized algorithm for SST retrieval.

• Korean Journal of Remote Sensing
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• v.24 no.4
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• pp.309-324
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• 2008

In this study the retrieval algorithms have been developed to retrieve total precipitable water (TPW) from Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) infrared measurements using a physical iterative retrieval method and a split-window technique over East Asia. Retrieved results from these algorithms were validated against Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) over ocean and radiosonde observation over land and were analyzed for investigating the key factors affecting the accuracy of results and physical processes of retrieval methods. Atmospheric profiles from Regional Data Assimilation and Prediction System (RDAPS), which produces analysis and prediction field of atmospheric variables over East Asia, were used as first-guess profiles for the physical retrieval algorithm. We used RTTOV-7 radiative transfer model to calculate the upwelling radiance at the top of the atmosphere. For the split-window technique, regression coefficients were obtained by relating the calculated brightness temperature to the paired radiosonde-estimated TPW. Physically retrieved TPWs were validated against SSM/I and radiosonde observations for 14 cases in August and December 2004 and results showed that the physical method improves the accuracy of TPW with smaller bias in comparison to TPWs of RDAPS data, MODIS products, and TPWs from split-window technique. Although physical iterative retrieval can reduce the bias of first-guess profiles and bring in more accurate TPWs, the retrieved results show the dependency upon initial guess fields. It is thought that the dependency is due to the fact that the water vapor absorption channels used in this study may not reflect moisture features in particular near surface.

• Korean Journal of Remote Sensing
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• v.24 no.1
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• pp.65-78
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• 2008

This study compares the relative accuracy and consistency of four split-window land surface temperature (LST) algorithms (Becker and Li, Kerr et ai., Price, Ulivieri et al.) using 24 sets of Terra (Aqua)/Moderate Resolution Imaging Spectroradiometer (MODIS) data, observed ground grass temperature and air temperature over South Korea. The effective spectral emissivities of two thermal infrared bands have been retrieved by vegetation coverage method using the normalized difference vegetation index. The intercomparison results among the four LST algorithms show that the three algorithms (Becker-Li, Price, and Ulivieri et al.) show very similar performances. The LST estimated by the Becker and Li's algorithm is the highest, whereas that by the Kerr et al.'s algorithm is the lowest without regard to the geographic locations and seasons. The performance of four LST algorithms is significantly better during cold season (night) than warm season (day). And the LST derived from Terra/MODIS is closer to the observed LST than that of Aqua/MODIS. In general, the performances of Becker-Li and Ulivieri et al algorithms are systematically better than the others without regard to the day/night, seasons, and satellites. And the root mean square error and bias of Ulivieri et al. algorithm are consistently less than that of Becker-Li for the four seasons.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.9
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• pp.1650-1657
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• 2007

In this paper, we propose an Overlapped Block and an Hanning Window to prevent a Block Discontinuity when we use an algorithm to eliminate ringing artifact which is based on a block structure. The algorithm to eliminate ringing artifact operates with a block structure and 24-RGB data and is based on a modified K-means algorithm. The proposed overlapped block method is piled up one on another per an half of the size of unit-block when an input image is split into several unit-blocks. Therefore, we define a data unit as the unit-block of the block size, $16{\times}16$ pixels. We reconstruct the processed data units into the original form of input image by using an isotropic form of Hanning Window. Finally, in order to evaluate the performance of the abovementioned algorithms, we compare three image, an input image with ringing artifact, an image result obtained by conventional method (non-overlapped), and an image result obtained the proposed method.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.293-296
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• 2008

Land surface Temperature (LST) is a very useful surface parameter for the wide range of applications, such as agriculture, numerical and climate modelling community. Whereas operational observation of LST is far from the needs of application community in the spatial Itemporal resolution and accuracy. So, we developed split-window type LST retrieval algorithm to estimate the LST from MTSAT-IR data. The coefficients of split-window algorithm were obtained by means of a statistical regression analysis from the radiative transfer simulations using MODTRAN 4 for wide range of atmospheric profiles, satellite zenith angle and lapse rate conditions including the surface inversions. The sensitivity analysis showed that the LST algorithm reproduces the LST with a reasonable quality. However, the LST algorithm overestimates and underestimates for the strong surface inversion and superadiabatic conditions especially for the warm temperature, respectively. And the performance of LST algorithms is superior when satellite zenith angle is small. The accuracy of the retrieved LST has been evaluated with the Moderate Resolution Imaging Spectroradiometer (MODIS) LST data. The validation results showed that the correlation coefficients and RMSE are about 0.83${\sim}$0.98 and 1.38${\sim}$4.06, respectively. And the quality of LST is significantly better during night and winter time than during day and summer. The validation results showed that the LST retrieval algorithm could be used for the operational retrieval of LST from MTSAT-IR and COMS(Communication, Ocean and Meteorological Satellite) data with some modifications.

• Proceedings of the KSRS Conference
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• 2008.03a
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• pp.164-169
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• 2008

한국해양연구원에서 수신한 자료인 NOAA 12, 16, 17, 18호등의 Advanced Very High Resolution Radiometer(AVHRR) 센서자료와 국립조사원에서 제공하는 해양실측자료인 정선 관측 자료를 이용하여 두 가지의 알고리즘 적용을 통하여 비교 및 분석을 해보고자 한다. 연구 기간은 2006년 1월부터 4월 자료 중 구름의 영향이 없는 영상에서 실측자료와 동일한 날짜 총 107개의 정점 값을 추출하였다. 위성 자료에서 해수면 온도 추출방법은 split window 방법으로, 고정계수 값을 사용하는 linear algorithm(MCSST), nonlinear algorithm(NLMCSST)을 이용하였다. 연구 지역은 동해, 황해, 남해 지역에 대한 지역별로 두 알고리즘을 비교 적용하였다. 전 해역의 값을 이용하여 위성자료와 실측자료를 비교 분석한 결과 linear algorithm방법의 평균 오차 값은 0.71$^{\circ}C$이고 상관도는 1%이고, nonlinear 방법의 오차 값은 0.35$^{\circ}C$ 상관도는 1%로 나타났다. 해역별로는 linear한 알고리즘을 적용하여 동해는(ES)는 R=1, 오차 값은 0.37$^{\circ}C$ 황해(YS)는 R=0.99 오차 값은 0.125$^{\circ}C$ 남해(SS)는 R=0.99 오차 값은 1.2$^{\circ}C$보였다. nonlinear한 알고리즘을 적용하여 동해는(ES)는 R=1, 오차 값은 0.4$^{\circ}C$ 황해(YS)는 R=0.99 오차 값은 0.13$^{\circ}C$ 남해(SS)는 R=0.99 오차 값은 0.82$^{\circ}C$의 결과를 보여 주었다. 동해와 황해지역은 linear한 알고리즘을 적용한 결과가 실측자료와의 오차 값이 작았고, 남해지역은 linear한 알고리즘을 적용한 결과보다 nonlinear 알고리즘을 적용한 것이 작은 오차 값을 보여주었다. 이는 남해 해역의 자료가 대기의 상태나 다른 영향을 받아 해수면온도 값이 추정된 것으로 보여 진다. 해역별로 최적화된 알고리즘을 적용하여 해수면온도의 산출을 통해서 위성자료의 정밀도 지구환경변화 모니터링 등 많은 연구에 위성자료의 활용이 증대될 것으로 기대한다.

• Journal of Mechanical Science and Technology
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• v.16 no.4
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• pp.427-435
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• 2002

This paper presents a development result for image processed tracking system of multiple moving objects based on Kalman filter and a simple window tracking method. The proposed algorithm of foreground detection and background adaptation (FDBA) is composed of three modules: a block checking module(BCM), an object movement prediction module(OMPM), and an adaptive background estimation module (ABEM). The BCM is processed for checking the existence of objects. To speed up the image processing time and to precisely track multiple objects under the object's mergence, a concept of a simple window tracking method is adopted in the OMPM. The ABEM separates the foreground from the background in the reset simple tracking window in the OMPM. It is shown through experimental results that the proposed FDBA algorithm is robustly adaptable to the background variation in a short processing time. Furthermore, it is shown that the proposed method can solve the problems of mergence, cross and split that are brought up in the case of tracking multiple moving objects.

• Proceedings of the KSRS Conference
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• v.1
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• pp.250-252
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• 2006

The land surface temperature (LST) can be defined as a weighted average temperature of components which constitute a pixel. The coefficients of split-window algorithm for MTSAT-1R were obtained by means of a statistical regression analysis from radiative transfer simulations using MODTRAN 4.0 for a wide range of atmospheric, satellite viewing angle (SVA) and lapse rate conditions. 6 types of atmospheric profile data imbedded in the MODTRAN 4 are used for the radiative transfer simulations. The RMSE is clearly larger on warm and humid profiles than cold and dry profiles, especially when the satellite viewing angle and lapse rate are large. The derivation of LST equations according to the atmospheric profiles clearly decreased the RMSE without regard to the SVA and lapse rate. The bias and RMSE are decreased as the more controls factors included. This preliminary result indicates that the characteristics of atmosphere, SVA and lapse rate should be included in the LST equation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.3
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• pp.546-555
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• 2013

In this paper, we propose a novel method to enhance the harmonic components from the frequency lines of the passive sonar signals. For this, we first separate the stable frequency lines from unstable ones using mean and difference of spectral bins in the vernier analysis. Then we emphasize the harmonic components using autocorrelation-based postprocessing, and enhance them by reducing the background noise with the split-window two pass mean algorithm. Experimental results for real underwater acoustic data are presented with our discussions.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.385-388
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• 2006

The land surface temperature (LST) can be defined as a weighted average temperature of components which constitute a pixel. The coefficients of split-window algorithm for MTSAT-1R were obtained by means of a statistical regression analysis from radiative transfer simulations using MODTRAN 4.0 for a wide range of atmospheric, satellite viewing angle (SVA) and lapse rate conditions. 6 types of atmospheric profile data imbedded in the MODTRAN 4 are used for the radiative transfer simulations. The RMSE is clearly larger on warm and humid profiles than cold and dry profiles, especially when the satellite viewing angle and lapse rate are large. The derivation of LST equations according to the atmospheric profiles clearly decreased the RMSE without regard to the SVA and lapse rate. The bias and RMSE are decreased as the more controls factors included. This preliminary result indicates that the characteristics of atmosphere, SVA and lapse rate should be included in the LST equation.