• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.4
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• pp.223-229
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• 2011

In this study, two types of LED spot light with the development of the current broadcast studio-light is installed in the space being used in many products, companies in the UK Arri-650W, 1000W Fresnel spot light and illumination, color temperature and color rendering comparison of data measured compared with the target of the shooting and the color rendition on images was measured by comparing the color. In the future, broadcast - shooting LED spot light replacing whether the available studies on the performance evaluation were analyzed. Experimental evaluation of a replacement for halogen lights in LED Spot light is potential was confirmed.

• Journal of Information Processing Systems
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• v.19 no.6
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• pp.791-802
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• 2023

The manual inspection of photovoltaic (PV) panels to meet the requirements of inspection work for large-scale PV power plants is challenging. We present a hot spot detection and positioning method to detect hot spots in batches and locate their latitudes and longitudes. First, a network based on the YOLOv3 architecture was utilized to identify hot spots. The innovation is to modify the RU_1 unit in the YOLOv3 model for hot spot detection in the far field of view and add a neural network residual unit for fusion. In addition, because of the misidentification problem in the infrared images of the solar PV panels, the DeepLab v3+ model was adopted to segment the PV panels to filter out the misidentification caused by bright spots on the ground. Finally, the latitude and longitude of the hot spot are calculated according to the geometric positioning method utilizing known information such as the drone's yaw angle, shooting height, and lens field-of-view. The experimental results indicate that the hot spot recognition rate accuracy is above 98%. When keeping the drone 25 m off the ground, the hot spot positioning error is at the decimeter level.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1999.10c
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• pp.765-770
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• 1999

The purpose of this study is to obtain land classification map by using remotely sensed data; Landsat TM and SPOT panchromatic, and to compare their results with statistical data and digitized coverage from topographic paper map. The classification was conducted by maximum likelihood method with training sets. The best result was obtained from the Landsat TM merged by SPOT Panchromatic, that is, similar with statistical data. This is caused by setting more precise training sets with the enhanced spatial resolution by using SPOT Panchromatic. The classified map may be useful as a fundamental data to estimate pollutant load in regional scale of agricultural watershed.

• Journal of Korean Society for Geospatial Information Science
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• v.11 no.2 s.25
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• pp.29-37
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• 2003

An approach is described for automatic measuring of GCP's image coordinates from SPOT imagery and focused on the fulfillment an automatic orientation of satellite images. For the orientation of a stereopair of digital images, firstly, GCP(Ground Control Point) should be selected and then the work for measuring of image coordinates correspond to GCPs is required. In this study, we propose the method for extracting the GCP's image coordinates automatically using an image patch for control points and auxiliary points matching. For the evaluation of measurement accuracy, a comparison between points those are extracted manually and automatically by a proposed method have made. Finally, we shows the feasibility of automatic image coordinates measurment by applying in stereo modeling for SPOT images.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.2
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• pp.114-124
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• 2014

For classifying fire damaged areas and analyzing burn severity of two large-fire areas damaged over 100 ha in 2011, three methods were employed utilized supervised classification, unsupervised classification and Normalized Difference Vegetation Index (NDVI). In this paper, the post-fire imageries of SPOT were used to compute the Maximum Likelihood (MLC), Minimum Distance (MIN), ISODATA, K-means, NDVI and to evaluate large-scale patterns of burn severity from 1 m to 5 m spatial resolutions. The result of the accuracy verification on burn severity from satellite images showed that average overall accuracy was 88.38 % and the Kappa coefficient was 0.8147. To compare the accuracy between burn severity and field survey at Uljin and Youngduk, two large fire sites were selected as study areas, and forty-four sampling plots were assigned in each study area for field survey. The burn severities of the study areas were estimated by analyzing burn severity (BS) classes from SPOT images taken one month after the occurrence of the fire. The applicability of composite burn index (CBI) was validated with a correlation analysis between field survey data and burn severity classified by SPOT5, and by their confusion matrix. The result showed that correlation between field survey data and BS by SPOT5 were closely correlated in both Uljin (r = -0.544 and p<0.01) and Youngduk (r = -0.616 and p<0.01). Thus, this result supported that the proposed burn severity analysis is an adequate method to measure burn severity of large fire areas in Korea.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.543-547
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• 2002

In this paper, we introduce a more improved camera modeling method for linear pushbroom images than the method proposed by Orun and Natarajan(ON). ON model shows an accuracy of within 1 pixel if more than 10 ground control points(GCPs) are provided. In general, there is high correlation between platform position and attitude parameters but ON model ignores attitude variation in order to overcome such correlation. We propose a new method that obtains an optimal solution set of parameters without ignoring the attitude variation. We first assume that attitude parameters are constant and estimate platform position's. Then we estimate platform attitude parameters using the values of estimated position parameters. As a result, we can set up an accurate camera model for a linear pushbroom satellite scene. In particular, we can apply the camera model to its surrounding scenes because our model provide sufficient information on satellite's position and attitude not only for a single scene but also for a whole imaging segment. We tested on two images: one with a pixel size 6.6m$\times$6.6m acquired from EOC(Electro Optical Camera), and the other with a pixel size 10m$\times$l0m acquired from SPOT. Our camera model procedures were applied to the images and gave satisfying results. We had obtained the root mean square errors of 0.5 pixel and 0.3 pixel with 25 GCPs and 23 GCPs, respectively.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.1
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• pp.61-69
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• 2009

By the advent of the high resolution satellite imagery, a ground-coverage included by a single satellite image is decreased. By the reason, there are increasing needs in image mosaicking technology to use images to various GIS fields. This paper describes an edge-based seamline extraction algorithm using edge information such as rivers, roads, buildings for image mosaicking. For this, we developed a method to track and link discontinuous edges extracted by edge detection operator. To estimate the effectiveness of the proposed algorithm, we applied the algorithm to IKONOS, KOMPSAT-1 and SPOT-5 satellite images. The experimental results showed that the algorithm successfully dealts with discontinuities caused by geometric differences in two images.

• Proceedings of KOSOMES biannual meeting
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• 2006.05a
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• pp.47-52
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• 2006

The cultural grounds of laver has been surveyed using SPOT-5 satellite images to calculate the facilities of laver cultivation area in the coastal waters of Korea 10m resolution multispectral images of SPOT-5 are adopted for the south area of Daebu Island, Hwaseong city to develop an automatic detection approach of laver nets that consists of the following: band difference technique, canny edge detector and morphological analysis. The satellite-based facilities number was relatively high as compared with the licensed number in 2005, 676,749 chaek and 572,745 chaek(柵, unit of measure for laver farm), respectively. The data could be applied to achieve a good harvest for laver seaweed growers and to control its national production keeping a stable market price for the government body.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.4 s.38
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• pp.27-36
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• 2006

Conventionally, in order to get accurate geolocation of satellite images we need a set of ground control points with respect to individual scenes. In this paper, we tested the possibilities of modeling satellite orbits from individual scenes by establishing a sensor model for one scene and by applying the model, which was derived from the same orbital segment, to other scenes that has been acquired from the same orbital segment. We investigated orbit-attitude models with several interpolation methods and with various parameter sets to be adjusted. We used 7 satellite images of SPOT-3 with a length of 420km and ground control points acquired from GPS surveying. Results of the conventional individual scene modeling hardly introduced differences among different interpolation methods and different adjustment parameter sets. As the results of orbit modeling, the best model was the one with Lagrange interpolation for position/velocity and linear interpolation for attitude and with position/angle bias as parameter sets. The best model showed that it is possible to model orbital segments of 420km with ground control points measured within one scene (60km).

• Journal of the Korea Institute of Military Science and Technology
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• v.8 no.4 s.23
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• pp.110-119
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• 2005

In this paper, a new detection algorithm was proposed for finding the position of lenslet array spot pattern used to acquire laser wavefront. Based on the analysis of the required signal processing characteristics, we categorized into and designed four main signal processing functions. The proposed was designed in order to have robust feature against a variation of geometrical form of the spot and also implemented to have semi-automatic thresholding capability based on CCD noise analysis. For performance evaluation, we made qualitative and quantitative comparisons with Carvalho's algorithm which has been published in recent. In the given experimental spot images, the proposed could detect the spots which has 1/3 times lower than the least S/N of which Carvalho's can detect and could reach to a detection precision of 0.1 pixel at the S/N. In functional aspect, the proposed could separate all valid spots locally. From these results, the proposed could have a superior precision of location detection of spot pattern in wider S/N range.