• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.21 no.2
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• pp.165-172
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• 2003

IKONOS satellite images are particularly well suited for stereo feature extraction. But, because IKONOS doesn't offer information about the satellite ephemeris and attitude, we have to use IKONOS RPC(Rational Polynomial Coefficients) data for 3-D feature extraction. In this study, it was intended to increase the accuracy and the efficiency in application of high resolution satellite images. Therefore, this study develop the program to extract 3-D feature information and have analyzed the geometric accuracy of the IKONOS satellite images by means of the change with the number, distribution and height of GCPs. This study will provide basic information for luther studies of the accuracy correction in IKONOS and high resolution satellite images.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.5
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• pp.413-422
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• 2018

Many applications using satellite data from high-resolution multispectral sensors require an image fusion step, known as pansharpening, before processing and analyzing the multispectral images when spatial fidelity is crucial. Image fusion methods are to improve images with higher spatial and spectral resolutions by reducing spectral distortion, which occurs on image fusion processing. The image fusion methods can be classified into MRA (Multi-Resolution Analysis) and CSA (Component Substitution Analysis) approaches. To suggest the efficient image fusion method for Pleiades and KOMPSAT (Korea Multi-Purpose Satellite) 3 satellites, this study will evaluate image fusion methods for multispectral and panchromatic images. HPF (High-Pass Filtering), SFIM (Smoothing Filter-based Intensity Modulation), GS (Gram Schmidt), and GSA (Adoptive GS) were selected for MRA and CSA based image fusion methods and applied on multispectral and panchromatic images. Their performances were evaluated using visual and quality index analysis. HPF and SFIM fusion results presented low performance of spatial details. GS and GSA fusion results had enhanced spatial information closer to panchromatic images, but GS produced more spectral distortions on urban structures. This study presented that GSA was effective to improve spatial resolution of multispectral images from Pleiades 1A and KOMPSAT 3.

• Proceedings of the KSRS Conference
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• v.2
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• pp.698-701
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• 2006

Remotely sensed data have been utilized efficiently for damage detection immediately after the natural disaster since they provide valuable information on land cover change due to spatial synchronization and multitemporal observation over large areas. Damage information obtained at an early stage is important for rapid emergency response and recovery works. Many useful techniques to analyze the characteristics of the pre- and post-event satellite images in large-scale damage detection have been successfully investigated for emergency management. Since high-resolution satellite images provide a wealth of information on damage occurred in urban areas, they are successfully utilized for damage detection in urban areas. In this research, a method to perform automated damage detection is proposed based on the differences of the textural characteristics in pre- and post- high resolution satellite images.

• Proceedings of the Korea Water Resources Association Conference
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• 2004.05b
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• pp.1271-1275
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• 2004

The purpose of this study is to present a standardized scheme for providing agriculture-related information at various spatial resolutions of satellite images including Landsat +ETM, KOMPSAT-1 EOC, ASTER VNIR, and IKONOS panchromatic and multi-spectral images. The satellite images were interpreted especially for identifying agricultural areas, crop types, agricultural facilities and structures. The results were compared with the land cover/land use classification system suggested by Ministry of Construction & Transportation based on NGIS (National Geographic Information System) and Ministry of Environment based on satellite remote sensing data. As a result, high-resolution agricultural land cover map from IKONOS imageries was made out. The results by IKONOS image will be provided to KOMPSAT-2 project for agricultural application.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.2
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• pp.121-132
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• 2016

This study proposes an approach for simulating high spatial resolution satellite images acquired under arbitrary sun-sensor geometry using existing images and 3D (three-dimensional) data. First, satellite images, having significant differences in spectral regions compared with those in the simulated image were transformed to the same spectral regions as those in simulated image by using the UPDM (Universal Pattern Decomposition Method). Simultaneously, shadows cast by buildings or high features under the new sun position were modeled. Then, pixels that changed from shadow into non-shadow areas and vice versa were simulated on the basis of existing images. Finally, buildings that were viewed under the new sensor position were modeled on the basis of open library-based 3D reconstruction program. An experiment was conducted to simulate WV-3 (WorldView-3) images acquired under two different sun-sensor geometries based on a Pleiades 1A image, an additional WV-3 image, a Landsat image, and 3D building models. The results show that the shapes of the buildings were modeled effectively, although some problems were noted in the simulation of pixels changing from shadows cast by buildings into non-shadow. Additionally, the mean reflectance of the simulated image was quite similar to that of actual images in vegetation and water areas. However, significant gaps between the mean reflectance of simulated and actual images in soil and road areas were noted, which could be attributed to differences in the moisture content.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.3
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• pp.125-132
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• 2017

Even after applying an image registration, Very High Resolution (VHR) multi-temporal images acquired from different optical satellite sensors such as IKONOS, QuickBird, and Kompsat-2 show a local misalignment due to dissimilarities in sensor properties and acquisition conditions. As the local misalignment, also referred to as Registration Noise (RN), is likely to have a negative impact on multi-temporal information extraction, detecting and reducing the RN can improve the multi-temporal image processing performance. In this paper, an approach to fine registration between VHR multi-temporal images by considering local distribution of RN is proposed. Since the dominant RN mainly exists along boundaries of objects, we use edge information in high frequency regions to identify it. In order to validate the proposed approach, datasets are built from VHR multi-temporal images acquired by optical satellite sensors. Both qualitative and quantitative assessments confirm the effectiveness of the proposed RN-based fine registration approach compared to the manual registration.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.533-540
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• 2021

High-resolution satellite images have high potential to acquire geospatial information over inaccessible areas such as Antarctica. Reference data are often required to increase the positional accuracy of the satellite data but the data are not available in many inland areas in Antarctica. Therefore this paper presents a multi-image RPCs (Rational Polynomial Coefficients) sensor modeling without any ground controls or reference data. Conjugate points between multi-images are extracted and used for the multi-image sensor modeling. The experiment was carried out for Kompsat-3A and showed that the significant accuracy increase was not observed but the approach has potential to suppress the maximum errors, especially the vertical errors.

• Current Industrial and Technological Trends in Aerospace
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• v.8 no.1
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• pp.45-54
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• 2010

The goal of the paper is to discuss the recent trend of the configuration of high resolution LEO(Low Earth Orbit) EO(Earth Observation) satellites. The satellite configuration is decided by considering several factors such as mission, payloads, launch vehicle, propulsion and attitude control module. The advent of commercial companies selling satellite's images in 2000's requires additional changes of the satellite system to be capable of obtaining many high resolution images quickly. In order to meet customer's needs, the overall configuration of satellites is designed to be compact and stable without the loss of structural integrity and reliability. Among design changes, the configuration change of satellites is treated intensively in the paper.

• Korean Journal of Remote Sensing
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• v.24 no.6
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• pp.631-639
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• 2008

This study presents an approach to synthesize hyperspectral images of lower resolution at a higher resolution using the high resolution images acquired from a sensor of commercial satellites. The proposed method was applied to the reconstruction of EO-1 Hyperion images using the images acquired from IKONOS sensor. Based on the FitPAN-Mod pansharpening technique (Lee, 2008b), the hyperspectral images of 30m resolution were reconstructed at 1m resolution of IKONOS panchromatic image. In this study, the synthesized hyperspectral images of 50 bands, whose wavelengths range in the wavelength of panchromatic sensor, were generated from the three stages of high resolution reconstruction using FitPAN-Mod. The experimental results show that the proposed method effectively integrates the spatial detail of the panchromatic modality as well as the spectral detail of the hyperspectral one into the synthesized image. It indicates the proposed method has a potential as a technique to produce alternative images for the images that would have been observed from a hyperspectral sensor at the high resolution of commercial satellite images.

• 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.