• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.3
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• pp.217-223
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• 2014

With precise sensor position, attitude element, and imaging resolution, a simulated geospatial image can be generated. In this study, a satellite image is simulated using SPOT ortho-image and global elevation data, and the geometric similarity between original and simulated images is analyzed. Using a SPOT panchromatic image and high-density elevation data from a 1/5K digital topographic map data an ortho-image with 10-meter resolution was produced. The simulated image was then generated by exterior orientation parameters and global elevation data (SRTM1, GDEM2). Experimental results showed that (1) the agreement of the image simulation between pixel location from the SRTM1/GDEM2 and high-resolution elevation data is above 99% within one pixel; (2) SRTM1 is closer than GDEM2 to high-resolution elevation data; (3) the location of error occurrence is caused by the elevation difference of topographical objects between high-density elevation data generated from the Digital Terrain Model (DTM) and Digital Surface Model (DSM)-based global elevation data. Error occurrences were typically found at river boundaries, in urban areas, and in forests. In conclusion, this study showed that global elevation data are of practical use in generating simulated images with 10-meter resolution.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.5
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• pp.449-457
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• 2011

As automated image processing techniques have been required in multi-temporal/multi-sensor geospatial image applications, use of automated but highly invariant image matching technique has been a critical ingredient. Note that there is high possibility of geometric and spectral differences between multi-temporal/multi-sensor geospatial images due to differences in sensor, acquisition geometry, season, and weather, etc. Among many image matching techniques, the SIFT (Scale Invariant Feature Transform) is a popular method since it has been recognized to be very robust to diverse imaging conditions. Therefore, the SIFT has high potential for the geospatial image processing. This paper presents a performance test results of the SIFT on geospatial imagery by simulating various image differences such as shear, scale, rotation, intensity, noise, and spectral differences. Since a geospatial image application often requires a number of good matching points over the images, the number of matching points was analyzed with its matching positional accuracy. The test results show that the SIFT is highly invariant but could not overcome significant image differences. In addition, it guarantees no outlier-free matching such that it is highly recommended to use outlier removal techniques such as RANSAC (RANdom SAmple Consensus).

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.5
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• pp.519-525
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• 2011

High-resolution earth-observing satellites acquire substantial amount of geospatial images. In addition to high image quality, high-resolution satellite images (HRSI) provide unprecedented direct georegistration accuracy, which have been enabled by accurate orbit determination technology. Direct georegistration is carried out by relating the determined position and attitude of camera to the ground target, i.e., projecting an image point to the earth ellipsoid using the collinearity equation. However, the apparent position of ground target is displaced due to the atmosphere and satellite velocity causing significant georegistration bias. In other words, optic ray from the earth surface to satellite cameras at 400~900km altitude refracts due to the thick atmosphere which is called atmospheric refraction. Velocity aberration is caused by high traveling speed of earth-observing satellites, approximately 7.7 km/s, relative to the earth surface. These effects should be compensated for accurate direct georegistration of HRSI. Therefore, this study presents the equation and the compensation procedure of atmospheric refraction and velocity aberration. Then, the effects are simulated at different image acquisition geometry to present how much bias is introduced. Finally, these effects are evaluated for Quickbird and WorldView-1 based on the physical sensor model.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.2
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• pp.87-95
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• 2008

Ladar (Laser Detection And Ranging, Lidar) is a sensor to acquire precise distances to the surfaces of target region using laser signals, which can be suitably applied to ATD (Automatic Target Detection) for guided missiles or aerial vehicles recently. It provides a range image in which each measured distance is expressed as the brightness of the corresponding pixel. Since the precise 3D models can be generated from the Ladar range image, more robust identification and recognition of the targets can be possible. If we simulate the data of Ladar sensor, we can efficiently use this simulator to design and develop Ladar sensors and systems and to develop the data processing algorithm. The purposes of this study are thus to simulate the signals of a Ladar sensor based on linear frequency modulation and to create range images from the simulated Ladar signals. We first simulated the laser signals of a Ladar using FM chirp modulator and then computed the distances from the sensor to a target using the FFT process of the simulated signals. Finally, we created the range image using the distances set.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.1
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• pp.81-88
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• 2015

Various satellite sensors having ranges of the visible, infrared, and thermal wavelengths have been launched due to the improvement of hardware technologies of satellite sensors development. According to the development of satellite sensors with various wavelength ranges, the fusion and integration of multisensor images are proceeded. Image matching process is an essential step for the application of multisensor images. Some algorithms, such as SIFT and SURF, have been proposed to co-register satellite images. However, when the existing algorithms are applied to extract matching points between optical and thermal images, high accuracy of co-registration might not be guaranteed because these images have difference spectral and spatial characteristics. In this paper, location of control points in a reference image is extracted by SURF, and then, location of their corresponding pairs is estimated from the correlation of the local similarity. In the case of local similarity, phase correlation method, which is based on fourier transformation, is applied. In the experiments by simulated, Landsat-8, and ASTER datasets, the proposed algorithm could extract reliable matching points compared to the existing SURF-based method.

• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.449-452
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• 2008

The building heights of big cities which charged with most space are 3-D information as relative vertical distance from ground control points, but they didn't know the heights using contour with maps as lose of skyline or building heights for downtown, practically continuously developed of many technology methods for implementation of 3-D spatial earth. So, For the view as stereos of variety earth form generated 3-D spatial and made terrain perspective map, 3-D simulated of regional and urban space as aviation images. In this papers, it composited geospatial informations and images by DEM generation, and developed and presented for techniques overlay of CAD data and photos captured at our surroundings uses. Particularly, The airborne LiDAR surveying which are very interesting trend have laser scanning sensor and determine the ground heights through detecting angle and range to the grounds, and then designated 3-D spatial composite and simulation from urban areas. Therefore in this papers are suggested ease selections on the users situation by compare as various simulations that its generation of 3-D spatial image by collective for downtown space and urban sub, and the implementation methods for more accurate, more select for the best images.

• Journal of Korean Society for Geospatial Information Science
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• v.2 no.2 s.4
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• pp.99-108
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• 1994

In this thesis, we propose the 3D terrain modelling method for the better understanding of the geographic information. The process of 3D terrain medelling consists of three steps. The first step is to obtain real-world data from satellite images and stored in the form of DEM(Digital Elevation Model). The second one is to extract the meaningful data from DEM data based on LOD(Level Of Detail). And the third is to construct the 3D surface by TIN(Triangulated Irregular Network) with the extracted meaingful data. The proposed dynamic TIN reconstruction algorithm locally reconstruct the existed TIN model with the additional a new point. In this way, we can construct the TIN with the reduced time and can simulated 3D terrain model in real time.