• Journal of Korean Society for Geospatial Information Science
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• v.11 no.2 s.25
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• pp.61-66
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• 2003

The change detection using the satellite imagery and airphotos has been carried out in the application of terrain mapping, environment, forestry, facility detection, etc. The low-spatial resolution data such as Landsat, NOAA satellite images is generally used for automatic change detection, while on the other hand the high-spatial resolution data is used for change detection by image interpretation. The research to integrate automatic method with manual change detection through the high-spatial resolution satellite image is performed. but the problem such as shadow, building 'lean' due to perspective geometry and precision geocorrection was found. In this paper we performed change detection using the IKONOS satellite images, and present the concerning problem.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.431-447
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• 2021

Recently, the use of high-resolution satellites is increasing in many areas. In order to supply useful satellite images stably, it is necessary to establish automatic precision geometric correction technic. Geometric correction is the process that corrected geometric errors of satellite imagery based on the GCP (Ground Control Point), which is correspondence point between accurate ground coordinates and image coordinates. Therefore, in the automatic geometric correction process, it is the key to acquire high-quality GCPs automatically. In this paper, we proposed iterative precision geometry correction method. we constructed an image pyramid and repeatedly performed GCP chip matching, outlier detection, and precision sensor modeling in each layer of the image pyramid. Through this method, we were able to acquire high-quality GCPs automatically. we then improved the performance of geometric correction of high-resolution satellite images. To analyze the performance of the proposed method, we used KOMPSAT-3 and 3A Level 1R 8 scenes. As a result of the experiment, the proposed method showed the geometric correction accuracy of 1.5 pixels on average and a maximum of 2 pixels.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.1
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• pp.125-132
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• 2024

Optical satellite images are being used for national security and collection of information, and their utilization is increasing. However, it acquires low-quality images that are not suitable for the user's requirement due to weather conditions and time constraints. In this paper, a deep learning-based conversion of image and colorization model referring to high-resolution SAR images was created to simulate the occluded area with clouds of optical satellite images. The model was experimented according to the type of algorithm applied and input data, and each simulated images was compared and analyzed. In particular, the amount of pixel value information between the input black-and-white image and the SAR image was similarly constructed to overcome the problem caused by the relatively lack of color information. As a result of the experiment, the histogram distribution of the simulated image learned with the Gray-scale image and the high-resolution SAR image was relatively similar to the original image. In addition, the RMSE value was about 6.9827 and the PSNR value was about 31.3960 calculated for quantitative analysis.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.559-564
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• 2002

This paper describes a new algorithm named as ray following algorithm which is applied for high-resolution satellite image simulation. The problems of the conventional ray tracing algorithm are pointed out especially when terrain elevations vary abruptly. The proposed algorithm follows the directional ray vector sequentially and thoroughly in order to determine the crossing point of the ray with the terrain surface. This way of sequential height comparison method is regarded as the only way to obtain accurate surface cross-section when a highly variant digital surface model is used. The experimental results show and compare the validities of the conventional and proposed algorithms.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.709-711
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• 2003

The purpose of this study is to detect the damaged red pine trees by pine wilt disease using high resolution satellite image of IKONOS Geo. IKONOS images are segmented with eCognition image processing software. A segment based maximum likelihood classification was performed to delineate the pine stand. The pine stands are regarded as a potential damage area. In order to develop a methodology to detect the location of damaged trees from the high resolution satellite image, black and white aerial photographs were used as a simulated image. The developed method based on filtering technique. A local maximum filter was adapted to detect the location of individual tree. This report presents a part of the first year results of an ongoing project.

• Korean Journal of Geomatics
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• v.3 no.1
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• pp.59-65
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• 2003

The merging of different scales or multi-sensor image data is becoming a widely used procedure of the complementary nature of various data sets. Ideally, the merging method should not distort the characteristics of the high-spatial and high-spectral resolution data used. To present an effective merging method for survey of reclaimed land using the high-resolution (6.6 m) Electro-Optical Camera (EOC) panchromatic image of the first Korea Multi-Purpose Satellite 1 (KOMPSA T-l) and the multispectral Moderate Resolution Imaging Spectroradiometer (MODIS) image data, this paper compares the results of Intensity Hue Saturation (IHS) and Principal Component Analysis (PCA) methods. The comparison is made by statistical and visual evaluation of three-color combination images of IHS and PCA results based on spatial and spectral characteristics. The use of MODIS bands 1, 2, and 3 with a contrast stretched EOC panchromatic image as a substitute for intensity was found to be particularly effective in this study.

• 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.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.3
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• pp.313-321
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• 2002

Supplying high-resolution satellite image, we take much interest in the update and the revision of digital map and thematic map based on the satellite image. This study presented the possibility of the update and the revision to the existing digital map on a scale of l/5,000 and 1/25,000 to take advantage of the IKONOS satellite image. We performed geometric correction to make use of the ground control points of the existing digital map in IKONOS mono-image and created ortho-image by extracting digital elevation model from three dimensional contour data and altitude on the existing digital map. We revised changed features in the method of screen digitizing by overlapping orthorectified satellite image and existing digital map and flawed features of the unchanged area on the satellite images for positional accuracy analysis. As a result, rectification error is calculated at $\pm$3.35m by RMSE. There is a good possibility of update of digital map under the scale of 1/10,000. It is possible to the update of the large scale digital map over the scale of l/5,000, as if we used the method of stereo image and ground control point surveying.

• Journal of the Korean Geographical Society
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• v.47 no.2
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• pp.282-296
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• 2012

This study compared effects of spatial resolution ratio in image fusion by Korea Multi-Purpose SATellite 2 (KOMPSAT II), also known as Arirang-2. Image fusion techniques, also called pansharpening, are required to obtain color imagery with high spatial resolution imagery using panchromatic and multi-spectral images. The higher quality satellite images generated by an image fusion technique enable interpreters to produce better application results. Thus, image fusions categorized in 3 domains were applied to find out significantly improved fused images using KOMPSAT 2. In addition, all fused images were evaluated to satisfy both spectral and spatial quality to investigate an optimum fused image. Additionally, this research compared Pixel-Based Image Analysis (PBIA) with the GEOgraphic Object-Based Image Analysis (GEOBIA) to make better classification results. Specifically, a roof top of building was extracted by both image analysis approaches and was finally evaluated to obtain the best accurate result. This research, therefore, provides the effective use for very high resolution satellite imagery with image interpreter to be used for many applications such as coastal area, urban and regional planning.

• Korean Journal of Remote Sensing
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• v.22 no.6
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• pp.621-626
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• 2006

Today's commercial high resolution satellite imagery such as IKONOS and QuickBird, offers the potential to extract useful spatial information for geographical database construction and GIS applications. Extraction of 3D building information from high resolution satellite imagery is one of the most active research topics. There have been many previous works to extract 3D information based on stereo analysis, including sensor modelling. Practically, it is not easy to obtain stereo high resolution satellite images. On single image performance, most studies applied the roof-bottom points or shadow length extracted manually to sensor models with DEM. It is not suitable to apply these algorithms for dense buildings. We aim to extract 3D building information from a single satellite image in a simple and practical way. To measure as many buildings as possible, in this paper, we suggested a new way to extract building height by triangular vector structure that consists of a building bottom point, its corresponding roof point and a shadow end point. The proposed method could increase the number of measurable building, and decrease the digitizing error and the computation efficiency.