• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.225-226
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• 2010

The problem in orthoimage generation is to recover occlusion areas. In this study, occlusion areas - double mapping regions of the building roofs - were mutually corrected by using multiple images. The proposed method could be efficient for generating true orthoimages in urban areas.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.1
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• pp.83-92
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• 2010

Emergence of high-resolution digital aerial cameras and airborne laser scanners have made innovative progress in photogrammetry and spatial information technology. The purpose of this study is to generate true orthoimage by recovering occlusion areas. The orthoimages were generated patch-based transformation. The occlusion areas were mutually corrected by using multiple aerial images. This study proposed a novel method of building roof based orthoimage generation and an effective method of occlusion area detection and recovery. The proposed methods could be efficient to generate true orthoimages in urban areas where occlusion areas are problematic.

• Spatial Information Research
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• v.19 no.3
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• pp.33-42
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• 2011

Since the method of generating 3D Spatial Information using aerial photographs was introduced, lots of researches on effective generation methods and applications have been performed. Nadir and oblique imagery are acquired in a same time by Pictometry system, and then 3D positioning is processed as Multi-Looking Camera procedure. In this procedure, the number of GCPs is the main factor which can affect the accuracy of true-orthoimage. In this study, 3D positioning accuracies of true-orthoimages which had been generated using various number of GCPs were estimated. Also, the standard of GCP number and distribution were proposed.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.339-353
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• 2023

As the availability of high-resolution satellite imagery increases, improvement of positioning accuracy of satellite images is required. The importance of orthorectified images is also increasing, which removes relief displacement and establishes true localization of man-made structures. In this paper, we performed automated extraction of building rooftops and total building areas within original satellite images using the existing building height database. We relocated the rooftop sin their true position and generated an orthorectified building layer. The extracted total building areas were used to blank out building areas and generate true orthographic non-building layer. A final orthorectified image was provided by overlapping the building layer and non-building layer.We tested the proposed method with KOMPSAT-3 and KOMPSAT-3A satellite images and verified the results by overlapping with a digital topographical map. Test results showed that orthorectified building layers were generated with a position error of 0.4m.Through the proposed method, the feasibility of automated true orthoimage generation within dense urban areas was confirmed.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.181-184
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• 2008

The quality of orthoimages mainly depends on the elevation information and exterior orientation (EO) parameters. Since LiDAR data directly provides the elevation information over the earth's surface including buildings and trees, the concept of true orthorectification has been rapidly developed and implemented. If a LiDAR-driven digital surface model (DSM) is used for orthorectification, the displacements caused by trees and buildings are effectively removed when compared with the conventional orthoimages processed with a digital elevation model (DEM). This study sequentially utilized LiDAR data to generate orthorectified digital aerial images. Experimental orthoimages were produced using DTM and DSM. For the preparation of orthorectification, EO components, one of the inputs for orthorectification, were adjusted with the ground control points (GCPs) collected from the LiDAR point data, and the ground points were extracted by a filtering method. The orthoimage generated by DSM corresponded more closely to non-ground LiDAR points than the orthoimage produced by DTM.

• Korean Journal of Remote Sensing
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• v.24 no.5
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• pp.463-471
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• 2008

The quality of orthoimages mainly depends on the elevation information and exterior orientation (EO) parameters. Since LiDAR data directly provides the elevation information over the earth's surface including buildings and trees, the concept of true orthorectification has been rapidly developed and implemented. If a LiDAR-driven digital surface model (DSM) is used for orthorectification, the displacements caused by trees and buildings are effectively removed when compared with the conventional orthoimages processed with a digital elevation model (DEM). This study utilized LiDAR data to generate orthorectified digital aerial images. Experimental orthoimages were produced using digital terrain model (DTM) and DSM. For the preparation of orthorectification, EO components, one of the inputs for orthorectification, were adjusted with the ground control points (GCPs) collected from the LiDAR point data, and the ground points were extracted by a filtering method used in a previous research. The orthoimage generated by DSM corresponded more closely to non-ground LiDAR points than the orthoimage produced by DTM.

• 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.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.4
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• pp.363-373
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• 2020

During last decades numerous studies generating orthoimage have been carried out. Traditional methods require exterior orientation parameters of aerial images and precise 3D object modeling data and DTM (Digital Terrain Model) to detect and recover occlusion areas. Furthermore, it is challenging task to automate the complicated process. In this paper, we proposed a new concept of true orthoimage generation using DL (Deep Learning). DL is rapidly used in wide range of fields. In particular, GAN (Generative Adversarial Network) is one of the DL models for various tasks in imaging processing and computer vision. The generator tries to produce results similar to the real images, while discriminator judges fake and real images until the results are satisfied. Such mutually adversarial mechanism improves quality of the results. Experiments were performed using GAN-based Pix2Pix model by utilizing IR (Infrared) orthoimages, intensity from LiDAR data provided by the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF) through the ISPRS (International Society for Photogrammetry and Remote Sensing). Two approaches were implemented: (1) One-step training with intensity data and high resolution orthoimages, (2) Recursive training with intensity data and color-coded low resolution intensity images for progressive enhancement of the results. Two methods provided similar quality based on FID (Fréchet Inception Distance) measures. However, if quality of the input data is close to the target image, better results could be obtained by increasing epoch. This paper is an early experimental study for feasibility of DL-based true orthoimage generation and further improvement would be necessary.

• Korean Journal of Remote Sensing
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• v.22 no.2
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• pp.131-139
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• 2006

IKONOS images have the perspective geometry in CCD sensor line like aerial images with central perspective geometry. So the occlusion by buildings, terrain or other objects exist in the image. It is difficult to detect the occlusion with RPCs(rational polynomial coefficients) for ortho-rectification of image. Therefore, in this study, we detected the occlusion areas in IKONOS images using the nominal collection elevation/azimuth angle and restored the hidden areas using another stereo images, from which the rue ortho image could be produced. The algorithm's validity was evaluated using the geometric accuracy of the generated ortho image.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.1
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• pp.53-62
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• 2016

In recent years, UAV Photogrammetry based on an ultra-light UAS(Unmanned Aerial System) installed with a low-cost compact navigation device and a camera has attracted great attention through fast and accurate acquirement of geo-spatial data. In particular, UAV Photogrammetry do gradually replace the traditional aerial photogrammetry because it is able to produce DEMs(Digital Elevation Models) and Orthophotos rapidly owing to large amounts of high resolution image collection by a low-cost camera and image processing software combined with computer vision technique. With these advantages, UAV-Photogrammetry has therefore been applying to a large scale mapping and cadastral surveying that require accurate position information. This paper presents experimental results of an accuracy performance test with images of 4cm GSD from a fixed wing UAS to demarcate parcel boundaries in agricultural area. Consequently, the accuracy of boundary point extracted from UAS orthoimage has shown less than 8cm compared with that of terrestrial cadastral surveying. This means that UAV images satisfy the tolerance limit of distance error in cadastral surveying for the scale of 1: 500. And also, the area deviation is negligible small, about 0.2%(3.3m²), against true area of 1,969m² by cadastral surveying. UAV-Photogrammetry is therefore as a promising technology to demarcate parcel boundaries.