• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.118-121
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• 2007

In recent years, the hyperspectral instruments with high spatial and high spectral resolution have become an important component of wide variety of earth science applications. The primary mission of the proposed Compact Airborne Imaging Spectrometer System (CAISS) in this study is to acquire and provide full contiguous spectral information with high quality spectral and spatial resolution for advanced applications in the field of remote sensing. The CAISS will also be used as the vicarious calibration equipment for the cross-calibration of satellite image data. The CAISS consists of six physical units: the camera system, the Jig, the GPS/INS, the gyro-stabilized mount, the operating system, and the power inverter and distributor. Additionally, the calibration instruments such as the integrated sphere and spectral lamps are also prepared for the radiometric and spectral calibration of the CAISS. The CAISS will provide high quality calibrated image data that can support evaluation of satellite application products. This paper summarizes the design, development and major characteristic of the CAISS.

• Journal of Korea Multimedia Society
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• v.22 no.3
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• pp.357-365
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• 2019

In this paper, we suggest the tracking method of moving multi-objects in maritime environments. The image acquisition is conducted using IR(InfraRed) camera sensors on an airborne platform. Under the circumstance of maritime, the qualities of IR images can be significantly degraded due to the clutter influence, which directly gives rise to a tracking loss problem. In order to reduce the effects from the clutters, we introduce a technical approach under Man-In-The-Loop(MITL) system for enhancing the tracking performance. To demonstrate the robustness of the proposed approach based on VTG(Valid Tracking Gate), the simulations are conducted utilizing the airborne IR video sequences: Then, the tracking performances are compared with the existing Kalman Filter tracking techniques.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.1
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• pp.46-55
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• 2006

The purpose of this study is a development of an automatic mosaicing for applying to large number of airborne multispectral images, which reduces manual operation by human. 2436 airborne multispectral images were acquired from DuncanTech MS4100 camera with three bands; green, red and near infrared. LIDAR(LIght Detection And Ranging) data and GPS/INS(global positioning system/inertial navigation system) data were collected with the multispectral images. First, the multispectral images were converted to image patterns by unsupervised classification. Their patterns were compared with those of adjacent images to derive relative spatial position between images. Relative spatial positions were derived for 80% of the whole images. Second, it accomplished an automatic mosaicing using GPS/INS data and unsupervised classification. Since the time of GPS/INS data did not synchronized the time of readout images, synchronized GPS/INS data with the time of readout image were selected in consecutive data by comparing unsupervised classified images. This method realized mosaicing automatically for 96% images and RMSE (root mean square error) for the spatial precision of mosaiced images was only 1.44 m by validation with LIDAR data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.1
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• pp.1-10
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• 2017

An UAV (Unmanned Aerial Vehicle) is a flight system that is designed to conduct missions without a pilot. Compared to traditional airborne-based photogrammetry, UAV-based photogrammetry is inexpensive and can obtain high-spatial resolution data quickly. In this study, we aimed to classify the land cover using high-spatial resolution images obtained using a UAV. An RGB camera was used to obtain high-spatial resolution orthoimage. For accurate classification, multispectral image about same areas were obtained using a multispectral sensor. A DSM (Digital Surface Model) and a modified NDVI (Normalized Difference Vegetation Index) were generated using images obtained using the RGB camera and multispectral sensor. Pixel-based classification was performed for twelve classes by using the RF (Random Forest) method. The classification accuracy was evaluated based on the error matrix, and it was confirmed that the proposed method effectively classified the area compared to supervised classification using only the RGB image.

• Korean Journal of Remote Sensing
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• v.30 no.6
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• pp.797-807
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• 2014

The Sea Surface Temperature (SST) is one of the most important oceanic environmental factors in determining the change of marine environments and ecological activities. Satellite thermal infrared images can be effective for understanding the global trend of sea surface temperature due to large scale. However, their low spatial resolution caused some limitations in some areas where complicated and refined coastal shapes due to many islands are present as in the Korean Peninsula. The coastal ocean is also very important because human activities interact with the environmental change of coastal area and most aqua farming is distributed in the coastal ocean. Thus, low-cost airborne thermal infrared remote sensing with high resolution capability is considered for verifying its possibility to extract SST and to monitor the changes of coastal environment. In this study, an airborne thermal infrared system was implemented using a low-cost and ground-based thermal infrared camera (FLIR), and more than 8 airborne acquisitions were carried out in the western coast of the Korean Peninsula during the periods between May 23, 2012 and December 7, 2013. The acquired thermal infrared images were radiometrically calibrated using an atmospheric radiative transfer model with a support from a temperature-humidity sensor, and geometrically calibrated using GPS and IMU sensors. In particular, the airborne sea surface temperature acquired in June 25, 2013 was compared and verified with satellite SST as well as ship-borne thermal infrared and in-situ SST data. As a result, the airborne thermal infrared sensor extracted SST with an accuracy of $1^{\circ}C$.

• Spatial Information Research
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• v.19 no.1
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• pp.51-59
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• 2011

We produced true ortho images after interpolating occlusion areas and relief displacement of building as well as producing ortho-images to use backward image of ADS which is a aerial digital camera of line type. Also, I was able to produce high quality ortho-images using a small mount of Ground Control Points(GCP) relatively to compare to frame type camera from the evaluation of horizontal position accuracy using ground check points, photo control points for the verification of ortho-images and true-ortho images. Also, I was able to verify the effectiveness in interpolating occlusion areas cause the length overlap was 100% when producing true-ortho images of line type camera.

• Korean Journal of Remote Sensing
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• v.14 no.3
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• pp.296-306
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• 1998

Airborne MSS data is regarded as a potentially effective data source for the measurement of water quality and for the environmental change of water bodies. In this study, we measured the radiance reflectance by using multi-spectral image of low resolution camera(LRC) which will be reached in the multi-purpose satellite(KOMPSAT) to use the data in analyzing water pollution. We also investigated the possibility of extraction of water quality factors in water bodies by using high resolution remote sensing data such as Airborne MSS. Especially, we tried to extract environmental factors related with eutrophication such as chlorophyll-a, suspended sediments and turbidity, and also tried to develop the process technique and the radiance feature of reflectance related with eutrophication. Although it was difficult to explicitly correlate Airborne MSS data with water quality factors due to the insufficient number of ground truth data. The results were summarized as follows: First, the spectrum of sun's rays which reaches the surface of the earth was consistent with visible bands of 0.4${\mu}{\textrm}{m}$~0.7${\mu}{\textrm}{m}$ and about 50% of total quantity of radiation could be found. The spectrum was reached highest at around 0.5${\mu}{\textrm}{m}$ of green spectral band in visible bands. Second, as a result of the radiance reflectance Chlorophyll-a represented high mainly around 0.52${\mu}{\textrm}{m}$ of green spectral band, and suspended sediments and turbidity represented high at 0.8${\mu}{\textrm}{m}$ and at 0.57${\mu}{\textrm}{m}$, respectively. Finally, as a result of the water quality analysis by using Airborne MSS, Chlorophyll-a could have a distribution image after carrying out ratio of B3 and B5 to B7. Band 7 was useful for making the distribution image of suspended sediments. When we carried out PCA, suspended sediments and turbidity had distributions at PC 1 and PC 4 which are similar to the ground data. Above results can be changed according to the change of season and time. Therefore, in order to analyze the environmental factors of water quality by using LRC data more exactly, we need to investigate the ground data and the radiance feature of reflectance of water bodies constantly. For further studies, we will constantly analyze the radiance feature of the surface of water in wafter bodies by measuring the on-the-spot radiance reflectance and using low resolution satellite image(SeaWiFS). We will also gather the data of water quality analysis in water bodies and analyze the pattern of water pollution.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.2
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• pp.181-188
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• 2012

The most recent, Digital photogrammetric camera, Airborne LiDAR and GPS/INS same sensors are used to acquire spatial information of various kinds in the field of aerial survey. In addition, Direct Georeferencing technology has been widely utilized with digital photogrammetric camera and GPS/INS. However, the sensor Calibration to be performed according to the combination of various sensors is followed by problems. Most of all, boresight calibration of integrated sensors is a critical element in the mapping process when using direct georeferencing or using the GPS/INS aerotriangulation. The establishment of a national test-bed in Sejong-si for aerial sensor calibration is absolutely necessary to solve this problem. And accurate calibration with used to integration of GPS/INS by aerotriangulation of aerial imagery was necessary for determination of system parameters, evaluation of systematic errors. Also, an investigation of efficient method for Direct georeferencing to determine the exterior orientation parameters and assessment of geometric accuracy of integrated sensors are performed.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.46-46
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• 2017

We developed a rice simulation model for remote-sensing (SIMRIW-RS, Homma et al., 2007) to evaluate rice production and management on a regional scale. Here, we reports its application trial to estimate rice production in farmers' fields in Sendai, Japan. The remote-sensing data for the application was periodically obtained by multispectral camera (RGB + NIR and RedEdge) attached with unmanned air vehicle (UAV). The airborne images was 8 cm in resolution which was attained by the flight at an altitude of 115 m. The remote-sensing data was relatively corresponded with leaf area index (LAI) of rice and its spatial and temporal variation, although the correspondences had some errors due to locational inaccuracy. Calibration of the simulation model depended on the first two remote-sensing data (obtained around one month after transplanting and panicle initiation) well predicted rice growth evaluated by the third remote-sensing data. The parameters obtained through the calibration may reflect soil fertility, and will be utilized for nutritional management. Although estimation accuracy has still needed to be improved, the rice yield was also well estimated. These results recommended further data accumulation and more accurate locational identification to improve the estimation accuracy.

• Korean Journal of Optics and Photonics
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• v.33 no.4
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• pp.146-158
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• 2022

The detector of a focal-plane-array mid-wave infrared (MWIR) camera has different response characteristics for each detector pixel, resulting in nonuniformity between detector pixels. In addition, image nonuniformity occurs due to heat generation inside the camera during operation. To solve this problem, in the process of camera manufacturing it is common to use a gain-and-offset table generated from a blackbody to correct the difference between detector pixels. One method of correcting nonuniformity due to internal heat generation during the operation of the camera generates a new offset value based on input frame images. This paper proposes a technique for dividing an input image into block image patches and generating offset values using only homogeneous patches, to correct the nonuniformity that occurs during camera operation. The proposed technique may not only generate a nonuniformity-correction offset that can prevent motion marks due to camera-gaze movement of the acquired image, but may also improve nonuniformity-correction performance with a small number of input images. Experimental results show that distortion such as flow marks does not occur, and good correction performance can be confirmed even with half the number of input images or fewer, compared to the traditional method.