• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.421-424
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• 1999

The purpose of this study is to demonstrate a variety of methods for reducing the speckle noise content of SAR images, whilst at the same time retaining the fined details and average radiometric properties of the original data. In order to increase the accuracy of classification, Two categories of filters are used (speckleblind(simple), Speckle aware(intelligent)) and Segmentation of highly speckled radar imagery is achieved by the use of the Gaussian Markov Random Field model(GMRF). The problems in applying filtering techniques to different object types are discussed and the GMRF procedure and efficiency of the segmentation also discussed.

• 한국태양에너지학회:학술대회논문집
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• 2008.11a
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• pp.161-166
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• 2008

The major purpose of this paper is to develop an uncertainty estimate for the calibration of thermopile instruments used to measure solar radiation parameters. We briefly describe the solar radiation parameters most often measured, instrumentation, reference standards, and calibration techniques. The bulk of the paper describes elemental sources of error and their magnitude. We then apply a standard error analysis methodology to combine these elemental error estimates into a statement of total uncertainty for the instrument calibration factor. Our results allow one to evaluate the accuracy of a radiometric measurement using thermopile instrumentation in the light of the application, such as engineering test evaluation or for validation of theoretical models.

• Journal of the Korean Solar Energy Society
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• v.21 no.3
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• pp.25-32
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• 2001

The major purpose of this paper is to develop an uncertainty estimate for the calibration of thermopile instruments used to measure solar radiation parameters. We briefly describe the solar radiation parameters most often measured, instrumentation, reference standards, and calibration techniques. The bulk of the paper describes elemental sources of error and their magnitude. We then apply a standard error analysis methodology to combine these elemental error estimates into a statement of total uncertainty for the instrument calibration factor. Our results allow one to evaluate the accuracy of a radiometric measurement using thermopile instrumentation in the light of the application, such as engineering test evaluation or for validation of theoretical models.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2004.03a
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• pp.255-259
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• 2004

본 논문에서는 다목적 위성 2호의 주 탑재체인 MSC (Multi-Spectral Camera)의 영상자료 검보정을 위한 검보정 target 준비 작업에 대해 설명한다. MSC 영상 자료에 대한 검보정 작업은 다목적 위성 2호의 발사 후 초기 운영 기간 (LEOP: Launch and Early Operation Phase)인 3개월 동안 수행될 예정이다. 위성 발사 전까지 MSC 영상 자료에 대한 검보정을 수행하기 위해 필요한 준비 작업들이 현재 한국항공우주연구원에서 진행중이다. LEOP 기간 동안 MSC 영상 자료를 검보정하기 위해서, MSC의 센서 특성에 따라 7가지 정도의 검보정 target에 대한 설계 초안이 완성되었으며, 향후 target에 대한 설계를 완성한 후에 2004년 중에 한 두 부지에 몇 가지 target들을 건설하고, 다목적 위성 2호의 궤도 특성을 고려하여 일부 target은 운반이 가능하도록 제작할 예정이다. 검보정 target이 촬영된 MSC 영상 자료의 분석을 통해, GSD (Ground Sample Distance), Aliasing, Linearity, Edge Slope & Response, MTF (Modulation Transfer Function), FOV & IFOV, Absolute radiometric validation, Position Accuracy 등의 MSC 검보정 요소 값들을 측정할 계획이다.

• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.1224-1227
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• 2009

When evaluating the quality of images and displays, it is important to combine the characteristics as perceived by the human visual system and measured by equipment using subjective and objective methods, respectively. In the case of objective methods, the quality of a display is measured using colorimetric or radiometric devices according to existing standards covering the color temperature, gamut size, gamma characteristic, and device characterization. Meanwhile, subjective methods assess the quality of an image using the human visual system based on a comparison with a reference or counterpart using such metrics as the sharpness, noise, contrast, saturation, and color accuracy. Objective and subjective methods are usually used together in comparison, as ultimately it is observers watching images on a display. In addition to existing objective methods, a new image quality metric is also introduced as regards the JPEG compression ratio that is reflected in the relationship between the gamut size and the color fidelity in CIELAB color space.

• Journal of Astronomy and Space Sciences
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• v.33 no.4
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• pp.313-318
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• 2016

Communication, Ocean And Meteorological Satellite (COMS) Meteorological Imager (MI) images are processed for radiometric and geometric correction from raw image data. When intermediate image data are matched and compared with reference landmark images in the geometrical correction process, various techniques for edge detection can be applied. It is essential to have a precise and correct edged image in this process, since its matching with the reference is directly related to the accuracy of the ground station output images. An edge detection method based on neural networks is applied for the ground processing of MI images for obtaining sharp edges in the correct positions. The simulation results are analyzed and characterized by comparing them with the results of conventional methods, such as Sobel and Canny filters.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.1
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• pp.49-58
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• 2012

Buildings become complex and diverse with time. It is difficult to extract individual buildings using only an optical image, because they have similar spectral characteristics to objects such as vegetation and roads. In this study, we propose a method to extract building area and boundary through integrating airborne Light Detection and Ranging(LiDAR) data and aerial images. Firstly, a binary edge map was generated using Edison edge detector after applying Adaptive dynamic range linear stretching radiometric enhancement algorithm to the aerial image. Secondly, building objects on airborne LiDAR data were extracted from normalized Digital Surface Model and aerial image. Then, a temporary building areas were extracted by overlaying the binary edge map and building objects extracted from LiDAR data. Finally, some building boundaries were additionally refined considering positional accuracy between LiDAR data and aerial image. The proposed method was applied to two experimental sites for validation. Through error matrix, F-measure, Jaccard coefficient, Yule coefficient, and Overall accuracy were calculated, and the values had a higher accuracy than 0.85.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.2
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• pp.159-172
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• 2006

In this study, the series of Landsat TM/ETM+ images was acquired to extract land surface temperature for wide-area and executed geometric correction and radiometric correction. And the land surface temperature was extracted using NASA Model, and achieved the first correction by performing land coverage category for study area and applied characteristic emission rate. Land surface temperature which was acquired by the first correction was analyzed in correlation with Meteorological Administration's temperature data by regression analysis, and established correction formula. And I wished to improve accuracy of land surface temperature extraction using satellite image by second correcting deviations between two data using establishing correction formula. As a result, land surface temperature acquired by 1st and 2st correction could be corrected in mean deviation of about ${\pm}3.0^{\circ}C$ with Meteorological Administration data. Also, I could acquire land surface temperature about study area by higher accuracy by applying to other Landsat images for re-verification of study results.

• Journal of the Optical Society of Korea
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• v.17 no.2
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• pp.213-218
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• 2013

Although infrared focal plane array (IRFPA) detectors have been commonly used, non-uniformity correction (NUC) remains an important problem in the infrared imaging realm. Non-uniformity severely degrades image quality and affects radiometric accuracy in infrared imaging applications. Residual non-uniformity (RNU) significantly affects the detection range of infrared surveillance and reconnaissance systems. More effort should be exerted to improve IRFPA uniformity. A novel NUC method that considers the surrounding temperature variation compensation is proposed based on the binary nonlinear non-uniformity theory model. The implementing procedure is described in detail. This approach simultaneously corrects response nonlinearity and compensates for the influence of surrounding temperature shift. Both qualitative evaluation and quantitative test comparison are performed among several correction technologies. The experimental result shows that the residual non-uniformity, which is corrected by the proposed method, is steady at approximately 0.02 percentage points within the target temperature range of 283 K to 373 K. Real-time imaging shows that the proposed method improves image quality better than traditional techniques.

• Proceedings of the KSRS Conference
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• v.2
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• pp.647-650
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• 2006

Compact Airborne Spectrographic Imager (CASI) hyperspectral imagery was acquired over the Little Miami River Watershed (1756 square miles) in Ohio, U.S.A., which is one of the largest hyperspectral image acquisition. For the development of a 4m-resolution land cover dataset, a hierarchical approach was employed using two different classification algorithms: 'Image Object Segmentation' for level-1 and 'Spectral Angle Mapper' for level-2. This classification scheme was developed to overcome the spectral inseparability of urban and rural features and to deal with radiometric distortions due to cross-track illumination. The land cover class members were lentic, lotic, forest, corn, soybean, wheat, dry herbaceous, grass, urban barren, rural barren, urban/built, and unclassified. The final phase of processing was completed after an extensive Quality Assurance and Quality Control (QA/QC) phase. With respect to the eleven land cover class members, the overall accuracy with a total of 902 reference points was 83.9% at 4m resolution. The dataset is available for public research, and applications of this product will represent an improvement over more commonly utilized data of coarser spatial resolution such as National Land Cover Data (NLCD).