• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.3
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• pp.211-218
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• 2015

The analysis of remote sensing data depends on sensor specifications that provide accurate and consistent measurements. However, it is not easy to establish confidence and consistency in data that are analyzed by different sensors using various radiometric scales. For this reason, the cross-calibration method is used to calibrate remote sensing data with reference image data. In this study, we used an airborne hyperspectral image in order to calibrate a multispectral image. We presented an automatic cross-calibration method to calibrate a multispectral image using hyperspectral data and spectral mixture analysis. The spectral characteristics of the multispectral image were adjusted by linear regression analysis. Optimal endmember sets between two images were estimated by spectral mixture analysis for the linear regression analysis, and bands of hyperspectral image were aggregated based on the spectral response function of the two images. The results were evaluated by comparing the Root Mean Square Error (RMSE), the Spectral Angle Mapper (SAM), and average percentage differences. The results of this study showed that the proposed method corrected the spectral information in the multispectral data by using hyperspectral data, and its performance was similar to the manual cross-calibration. The proposed method demonstrated the possibility of automatic cross-calibration based on spectral mixture analysis.

• The Transactions of the Korea Information Processing Society
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• v.7 no.3
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• pp.977-991
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• 2000

In this paper, a medical image processing system was designed and implemented for morphometric and functional analysis of a human brain. The system is composed of image registration, ROI(region of interest) analysis, functional analysis, image visualization, 3D medical image database management system(DBMS), and database. The software processes an anatomical and functional image as input data, and provides visual and quantitative results. Input data and intermediate or final output data are stored to the database as several data types by the DBMS for other further image processing. In the experiment, the ROI analysis, for a normal, a tumor, a Parkinson's decease, and a depression case, showed that the system is useful for morphometric and functional analysis of a human brain.

• Management & Information Systems Review
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• v.1
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• pp.401-412
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• 1997

Traditionally, classification of remote sensed image data is one of the important works for image data analysis procedure. So, many researchers have been devoted their endeavor to increasing accuracy of analysis, also, many classification algorithms have been proposed. In this paper, we propose new bands selection method for multispectral bands of remote sensed image data that use rough set theory. Using indiscernibility relations in rough sets, we show that can select the efficient bands of multispectral image data, automatically.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.205-208
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• 1997

Traditionally, classification of remote sensed image data is one of the important works for image data analysis procedure. So, many researchers devote their endeavor to increasing accuracy of analysis, also, many classification algorithms have been proposed. In this paper, we propose new classification method for remote sensed image data that use rough set theory. Using indiscernibility relation of rough sets, we show that can classify image data very easily.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.509-511
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• 2004

This paper outlines the development of image processing system, which will allow the general users in Government and Public organizations easily to use and apply KOMPSAT EOC images in their own business. The system includes an import/export module of EOC image distributed in Hierarchical Data Format (HDF) file and various image processing analysis modules. Especially, the image mosaic and subset functions are designed to use EOC image as an image map, generating the Ortho-image module. To update the various spatial data with EOC image, some essential modules such as change detection by pattern recognition, overlay between images and vector data, and modification of vector data are implemented in the system. The system is developed based on the user request analysis of government agency, and suited for more efficient use of satellite image in public applications. Such system is expected to contribute to practical application of KOMPSAT-2 that will be launched in 2005. Further efforts will be made to accommodate the KOMPSAT -2 MSC data.

• The Research Journal of the Costume Culture
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• v.12 no.1
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• pp.90-103
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• 2004

The purpose of the present study was to investigate images pursued and purchase behaviors for clothing as determined by self-image. Data were collected through a self-administered questionnaire survey from March 3 to March 11, 2003 from 600 female students attending universities in Seoul; 514 were used for the data analysis. Data were analyzed by chi-square analysis, t-test, ANOVA, correlation analysis, tics, cluster analysis and Duncan's multiple range test. Self image was defined six factors: social image, gay image, intellectual image, girlish image, iron nerves image, image like a man and was classified three group avail of six factor: commonness type, social brilliance type, immature boldness type. The results showed significant differences in images of actual clothing worn by self and in the clothing image pursued among the groups determined by the self image. Significant differences were also found in clothing purchase behaviors such as monthly clothing expenditure, shopping frequency, store types, and the clothing items often used for expressing self-image among the groups divided by self-image.

• Journal of Astronomy and Space Sciences
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• v.17 no.1
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• pp.117-122
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• 2000

The KOMPSAT(Korea Multi-Purpose SATellite) has two optical imaging instruments called EOC(Electro-Optical Camera) and OSMI (Ocean Scanning Multispectral Imager). The image data of these instruments are transmitted to ground station and restored correctly after post-processing with the telemetry data transfeered from KOMPSAT spacecraft. The major timing information of the KOMPSAT is OBT (On-Board Time) which is formatted by the on-board computer of the spacecraft, based on 1Hz sync. pulse coming from the GPS receiver involved. The OBT is transmitted to ground station with the house-keeping telemetry data of the spacecraft while it is distributed to the instruments via 1553B data bus for synchronization during imaging and formatting. The timing information contained in the spacecraft telemetry data would have direct relation to the image data of the instruments, which should be well explained to get a more accurate image. This paper addresses the timing analysis of the KOMPSAT spacecraft and instruments, including the gyro data timing analysis for the correct restoration of the EOC and OSMI image data at ground station.

• Proceedings of the KSRS Conference
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• v.1
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• pp.282-285
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• 2006

This paper analyzed the characteristics of the Lossy JPEG of the meteorological satellite image, and analyzed the quality of the Lossy JPEG compression, which is proper for the LRIT(Low Rate Information Transmission) to be serviced to the SDUS(Small-scale Data Utilization Station) system of the COMS(Communication, Oceans, Meteorological Satellite). Since COMS is to start running after 2008, we collected the data of the MTSAT-1R(Multi-functional Transport Satellite -1R) for analysis, and after forming the original image to be used to LRIT by each channel and time zone of the satellite image data, we set the different quality with the Lossy JPEG compression, and compressed the original data. For the characteristic analysis of the Lossy JPEG, we measured PSNR(Peak Signal to Noise Rate), compression rate and the time spent in compression following each quality of Lossy JPEG compression. As a result of the analysis of the satellite image data of the MTSAT-1R, the ideal quality of the Lossy JPEG compression was found to be 90% in the VIS Channel, 85% in the IR1 Channel, 80% in the IR2 Channel, 90% in the IR3 Channel and 90% in the IR4 Channel.

• Management & Information Systems Review
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• v.3
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• pp.15-45
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• 1999

Processing techniques of remote sensed image data using computer have been recognized very necessary techniques to all social fields, such as, environmental observation, land cultivation, resource investigation, military trend grasp and agricultural product estimation, etc. Especially, accurate classification and analysis to remote sensed image da are important elements that can determine reliability of remote sensed image data processing systems, and many researches have been processed to improve these accuracy of classification and analysis. Traditionally, remote sensed image data processing systems have been processed 2 or 3 selected bands in multiple bands, in this time, their selection criterions are statistical separability or wavelength properties. But, it have be bring up the necessity of bands selection method by data distribution characteristics than traditional bands selection by wavelength properties or statistical separability. Because data sensing environments change from multispectral environments to hyperspectral environments. In this paper for efficient data classification in multispectral bands environment, a band feature extraction method using the Rough sets theory is proposed. First, we make a look up table from training data, and analyze the properties of experimental multispectral image data, then select the efficient band using indiscernibility relation of Rough set theory from analysis results. Proposed method is applied to LANDSAT TM data on 2 June 1992. From this, we show clustering trends that similar to traditional band selection results by wavelength properties, from this, we verify that can use the proposed method that centered on data properties to select the efficient bands, though data sensing environment change to hyperspectral band environments.

• Journal of Industrial Technology
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• v.18
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• pp.17-25
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• 1998

Recently, there are a lot of studies to use a satellite image data in order to investigate a simultaneous change of a wide range area as a lake. However, many cases of a water quality research occur as problem when we try to extract the water quality factors from the satellite image data, because of the atmosphere scattering exert as bad influence on a result of analysis. In this study, and attempt was made to select the relative atmospheric correction method for the water quality factors extraction from the satellite image data. And also, the time-series analysis of the water quality factors extraction from the satellite image data. And also, the time-series analysis of the water quality factors was performed by using the multi-temporal image data.