• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.5
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• pp.315-322
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• 2019

DSM (Digital Surface Model) is a digital representation of ground surface topography or terrain that is widely used for hydrology, slope analysis, and urban planning. Aerial photogrammetry and LiDAR (Light Detection And Ranging) are main technology for urban DSM generation but high-resolution satellite imagery is the only ingredient for remote inaccessible areas. Traditional automated DSM generation method is based on correlation-based methods but recent study shows that a modern pixelwise image matching method, SGM (Semi-Global Matching) can be an alternative. Therefore this study investigated the application of SGM for Kompsat satellite data of KARI (Korea Aerospace Research Institute). Firstly, the sensor modeling was carried out for precise ground-to-image computation, followed by the epipolar image resampling for efficient stereo processing. Secondly, SGM was applied using different parameterizations. The generated DSM was evaluated with a reference DSM generated by the first pulse returns of the LIDAR reference dataset.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1493-1507
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• 2020

The LEOP Cal/Val (Launch and Early Operation Phase Calibration/Validation) was carried out during 6 months after KOMPSAT-3A (KOMPSAT-3A Korea Multi-Purpose Satellite-3A) was launched in March 2015. After LEOP Cal/Val was successfully completed, high resolution KOMPSAT-3A has been successfully distributing to users over the past 8 years. The sub-meter high-resolution satellite image data obtained from KOMPSAT-3A is used as basic data for qualitative and quantitative information extraction in various fields such as mapping, GIS (Geographic Information System), and national land management, etc. The KARI (Korea Aerospace Research Institute) periodically checks and manages the quality of KOMPSAT-3A's product and the characteristics of satellite hardware to ensure the accuracy and reliability of information extracted from satellite data of KOMPSAT-3A. To minimize the deterioration of image quality due to aging of satellite hardware, payload and attitude sensors of KOMPSAT-3A, continuous improvement of image quality has been carried out. In this paper, the Cal/Val work-flow defined in the KOMPSAT-3A development phase was illustrated for the period of before and after the launch. The MTF, SNR, and location accuracy are the key parameters to estimate image quality and the methods of the measurements of each parameter are also described in this work. On the basis of defined quality parameters, the performance was evaluated and measured during the period of after LEOP Cal/Val. The current status and characteristics of MTF, SNR, and location accuracy of KOMPSAT-3A from 2016 to May 2020 were described as well.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.664-669
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• 2002

Intertidal zone (tidal flat) is a place which is sometimes dry and sometimes wet depending on the tidal rhythm. Direct measurement of topography in the intertidal zone is very difficult to be achieved. The interface between wet and dry parts in the tidal flat, which can be identified from near infrared band of satellite image, is a 'depth contour' which corresponds to the sea level at the time of satellite pass. Aquisition of topography data in tidal flat is possible by combining various techniques such as (1) identification of the interface between wet and dry parts, (2) GCP correction of satellite image, and (3) realtime prediction of sea level elevation at the time of satellite pass. The algorithm was successfully applied in obtaining topography (bathymetry) data in the intertidal zone of Asan Bay in the west coast of Korea from 26 satellite images. The method is expected to be very efficient in making bathymetry data base in the western and southern parts of Korea where tidal flats are well developed in wide regions.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1999.10c
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• pp.519-524
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• 1999

In order to assess the estimtions of CN for a small agricultural watershed using the satellite image, TM image from Landsat-5 was classsified by MLC. CN for each pixels in the image was estimaed using the results. For the estimation enhancing , it was tried that each land use area in a pixel was estimated by the mixel assumption and the averaged CN by weight areas. Those resutls were applied for the actual hydrologic analyses were highly concerned with the observed runoff discharge and more enhanced on the mixel assumption.

• Journal of Advanced Navigation Technology
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• v.20 no.4
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• pp.380-385
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• 2016

Shadows are common phenomena observed in natural scenes and often bring a major problem that is affected negatively in colour image analysis. It is important to detect the shadow areas and should be considered in the pre-processing of computer vision. In this paper, the method of shadow detection is proposed using cross entropy and intensity image, and is performed in single image based on the satellite images. After converting the color image to a gray level image, the shadow candidate region has been estimated the optimal threshold value by cross entropy, and then the final shadow region has been detected using intensity image. For the validity of the proposed method, the satellite images is used to experiment. Some experiments are conducted so as to verify the proposed method, and as a result, shadow detection is well performed.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.9 no.2
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• pp.49-56
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• 1991

In this study, 3D positioning of CCT digital imagery was done by using a personal computer image processing method to increase the economic and time efficiency of SPOT satellite imagery. Image matching technique which applies statistical theories, was applied to acqusition of satellite imagery. The reliability of these coordinates was anlysed to presente a new algorithm for three dimensional positioning necessary in digital elevation modelling and orthophoto production. In acquiring image coordinates from CCT digital satellite imagery, accuracy of planimetric and height coordinates was improved by applying the image matching technique and it was found through analysis of correlation factors between sizes of target window that 19$\times$19 pixels was the most suitable size for image coordinate acquisition. From these results, it was able to present an algorithm about utility of digital imagery in the analysis of SPOT satellite data.

• Journal of Space Technology and Applications
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• v.3 no.3
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• pp.257-279
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• 2023

Korea Aerospace Research Institute has developed 6U Nano-Satellite high resolution video and image (HiREV) for the purpose of developing core technology for deep space exploration. The 6U HiREV Nano-Satellite has a mission of high-resolution image and video for earth observation, and the thermal pointing error between the lens and the camera module can occur due to the high temperature in camera module on mission mode. The thermal pointing error has a large effect on the resolution, so thermal design should solve it because the HiREV optical camera is developed based on commercial products that are the industrial level. So, when it operates in space, the thermal design is needed, because it has the best performance at room temperature. In this paper, three passive thermal designs were performed for the camera mission payload, and the thermal design was proved to be effective by performing on-orbit thermal analysis.

• Journal of the HCI Society of Korea
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• v.2 no.2
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• pp.35-43
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• 2007

This paper presents a system for image matching and recognition based on image feature detection and description techniques from artificial satellite photographs. We propose some kind of parameters from the varied environmental elements happen by image handling process. The essential point of this experiment is analyzes that affects match rate and recognition accuracy when to change of state of each parameter. The proposed system is basically inspired by Lowe's SIFT(Scale-Invariant Transform Feature) algorithm. The descriptors extracted from local affine invariant regions are saved into database, which are defined by k-means performed on the 128-dimensional descriptor vectors on an artificial satellite photographs from Google earth. And then, a label is attached to each cluster of the feature database and acts as guidance for an appeared building's information in the scene from camera. This experiment shows the various parameters and compares the affected results by changing parameters for the process of image matching and recognition. Finally, the implementation and the experimental results for several requests are shown.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.4
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• pp.81-88
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• 2007

The geometry of satellite image captured by linear CCD sensor is different from that of frame camera image. The fact that the exterior orientation parameters for satellite image with linear CCD sensor varies from scan line by scan line, causes the difference of image geometry between frame and linear CCD sensor. Therefore, we need the epipolar geometry for linear CCD image which differs from that of frame camera image. In this paper, we proposed a method of resampling linear CCD satellite image in epipolar geometry under the assumption that image is not formed in perspective projection but in parallel projection, and the sensor model is a 2D affine sensor model based on parallel projection. For the experiment, IKONOS stereo images, which are high resolution linear CCD images, were used and tested. As results, the spatial accuracy of 2D affine sensor model is investigated and the accuracy of epipolar resampled image with RFM was presented.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.1
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• pp.1-11
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• 2021

Detection of surface water features including river, wetland, reservoir from the satellite imagery can be utilized for sustainable management and survey of water resources. This research compared the water indices derived from the multispectral bands and the machine learning technique for detecting the surface water features from he Landsat-8 satellite image acquired in Daegu through the following steps. First, the NDWI(Normalized Difference Water Index) image and the MNDWI(Modified Normalized Difference Water Index) image were separately generated using the multispectral bands of the given Landsat-8 satellite image, and the two binary images were generated from these NDWI and MNDWI images, respectively. Then SVM(Support Vector Machine), the widely used machine learning techniques, were employed to generate the land cover image and the binary image was also generated from the generated land cover image. Finally the error matrices were used for measuring the accuracy of the three binary images for detecting the surface water features. The statistical results showed that the binary image generated from the MNDWI image(84%) had the relatively low accuracy than the binary image generated from the NDWI image(94%) and generated by SVM(96%). And some misclassification errors occurred in all three binary images where the land features were misclassified as the surface water features because of the shadow effects.