• Korean Journal of Remote Sensing
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• v.27 no.1
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• pp.51-58
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• 2011

Accurate DEM(Digital Elevation Model) generation using satellite images is an active research topic. This paper focuses on generation of a DEM with multiple Kompsat-2 images. For DEM generation, we applied an orbit-attitude sensor model and a RPM sensor model to stereo and multiple Kompsat-2 images respectively. For matching, we used an object-space based matching method. Through the result of this experiment, we could confirm that the sensor model from multiple images is more accurate than the model from stereo images. Also DEM from multiple images gave much better performance than DEM from stereo images.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.4
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• pp.241-248
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• 2017

GCPs (Ground Control Points) are needed to correct the DEM (Digital Elevation Model) produced from high-resolution satellite images and the RPC (Rational Polynomial Coefficient). It is difficult to acquire the GCPs through field surveys such as GPS surveys and to read the image coordinates corresponding to the GCPs. In addition, GCPs cannot cover the entire image of the test site, and the RPC correction results may be influenced by the arrangement and distribution of the GCPs in the image. Therefore, a new method for the RPC correction is needed. In this study, an LHD (Least-squares Height Difference) DEM matching method was applied using previous DEMs: SRTM DEM, digital map DEM, and corrected IKONOS DEM. This was carried out to correct the DEM produced from KOMPSAT-3 satellite images and the provided RPC without GCPs. The IKONOS DEM had the highest accuracy, and the height accuracy was about ${\pm}3m$ RMSE in a mountainous area and about ${\pm}2m$ RMSE in an area with only low heights.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.1
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• pp.751-760
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• 2009

This research aims to develop the strategy and method to enhance the reliability of image matching results and improve the efficiency of the matching process by utilizing LIDAR data in the main image matching processes. In this work, we present the methods to utilize LIDAR data in the selection of matching entities, the search for the matched entities and the evaluation of the matching results. The proposed method has been applied to medium-resolution digital aerial images and LIDAR data acquired at the same time. The results have been analyzed in comparison with an existing method using a virtual horizontal surface rather than LIDAR DEM. This analysis indicates that the proposed method can show significantly more improved performance than the existing method. The results of this study can contribute to the improvement of the currently available commercial image matching software and the enhancement of the DEM derived from LIDAR data and matching results.

• Korean Journal of Remote Sensing
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• v.13 no.2
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• pp.121-132
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• 1997

This paper describes the development of a stereo matching algorithm for extracting Digital Elevation Model(DEM) from satellite images. This matching algorithm is based on a non-linear least squares correlation estimation but has improved matching speed. The algorithm consists of three steps: matching execution, matching control and matching optimization. Each is described. The performance of the presented algorithm is quantitatively analyzed with experiments on matching probability, matching speed and matching convergence radius.

• Korean Journal of Remote Sensing
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• v.8 no.1
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• pp.15-26
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• 1992

This paper describes an implementation of adaptive stereo matching for DBM generation. The matching method of two stereo satellite images to find corresponding points used in this paper is area-based matching, which is usually used in the field of making DBM. Same window size and search area used as in the conventional matching methods and we propose adaptive stereo matching algorithm in this paper. We cluster three areas which are consist of mountainous areas, cultivated areas and cities, and rivers and lakes by using proposed linear feature extracting method. These classified areas are matched by adaptive window size and search area, but rivers and lakes is excluded in this experiment. The matching time is three times faster than conventional methods.

• Korean Journal of Remote Sensing
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• v.27 no.4
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• pp.411-420
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• 2011

In this study, a digital elevation model (DEM) in tidal flat of Suncheon Bay, one of the most ecological preserved area in the world, was generated from digital aerial stereo-images. The focal lengths for the aerial stereo-images were adjusted using ground control points (GCPs) in order to improve the accuracy of camera parameters. We proposed matching sizes suitable for generating DEM in tidal flat and a method for eliminating excessive position errors using intersection-distance($P_R$) threshold value. The accuracies of the DEM generated from the proposed method as well as the commercial S/W were compared with the elevation profiles measured by Total Station in the filed. As the results, the DEM generated by the proposed method showed better result (maximum deviation is a -21 centimeters) with detailed topography than DEM by the commercial S/W in the region. These results suggest that the DEM of tidal flat, which hardly obtained with the traditional methods, can be generated from digital aerial images by applying the proposed method in this study. We believe that the generated DEM in tidal flat can be an essential data for monitoring the sediment erosion and deposit of the tidal flat.

• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1445-1456
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• 2018

The purpose of this study is to compare the quality and characteristics of matching DEMs by using KOMPSAT-3 stereo pair capture in in-track and cross-track. For this purpose, two stereo pairs of KOMPSAT-3 were collected that were taken in the same area. The two stereo pairs have similar stereo geometry elements such as B/H, convergence angle. Sensor modeling for DEM production was performed with RFM affine calibration using multiple GCPs. The GCPs used in the study were extracted from the 0.25 m ortho-image and 5 meter DEM provided by NGII. In addition, matching DEMs were produced at the same resolution as the reference DEMs for a comparison analysis. As a result of the experiment, the horizontal and vertical errors at the CPs indicated an accuracy of 1 to 3 pixels. In addition, the shapes and accuracy of two DEMs produced in areas where the effects of natural or artificial surface land were low were almost similar.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.6_1
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• pp.583-590
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• 2012

This study proposes fusion image matching method according to land cover property to generate a detailed DEM using the high resolution IKONOS-2 stereo pair. A classified image, consists of building, crop-land, forest, road and shadow-water, is produced by color image with four bands. Edges and points are also extracted from panchromatic image. Matching is performed by the cross-correlation computing after five classes are automatically selected in a reference image. In each of building class, crop-land class, forest class and road class, matching was performed by the grid and edge, only grid, only grid, grid and point, respectively. Shadow-water class was excepted in the matching because this area causes excessive error of the DEM. As the results, edge line, building and residential area could be expressed more dense than DEM by the conventional method.

• Korean Journal of Remote Sensing
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• v.33 no.3
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• pp.325-331
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• 2017

In this study, digital elevation models(DEM) of tidal flat, according to different times, was produced by means of the Drone and commercial software in order to measure seawater change during high tide at water-channel in the Hampyung Bay. To correct the produced DEMs of the tidal flat where is inaccessible to collect control points, the DEM matching method was applied by using the reference DEM, that is previously obtained, instead of the survey. After the ortho-image was made from the corrected DEM, the land cover classified image was produced. The changes of seawater amount according to the times were analyzed by using the classified images and DEMs. As a result, it was confirmed that the amount of water rapidly increased as the time passed during high tide.

• Korean Journal of Remote Sensing
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• v.14 no.3
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• pp.250-261
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• 1998

The purpose of this paper is to extract fast DEM (Digital Elevation Model) using satellite images. DEM extraction consists of three parts. First part is the modeling of satellite position and attitude, second part is the matching of two images to find corresponding points of them and third part is to calculate the elevation of each point by using the results of the first and second part. The position and attitude modeling of satellite is processed by using GCPs. A area based matching method is used to find corresponding points between the stereo satellite images. The elevation of each point is calculated using the exterior orientation parameters obtained from modeling and conjugate points from matching. In the DEM generation system, matching procedure holds most of a processing time, therefore to reduce the time for matching, a new fast matching algorithm using gradient correlation and fast similarity measure calculation method is proposed. In this paper, the SPOT satellite images, level 1A 6000$\times$6000 panchromatic images are used to extract DEM. The experiment result shows the possibility of fast DEM extraction with the satellite images.