• Journal of the Korea Institute of Military Science and Technology
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• 제13권1호
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• pp.105-113
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• 2010

SAR(Synthetic Aperture Radar) has characteristics well-suited for the measurement of geophysical parameters during day and night in all weather conditions. Recently, SAR data with high resolution acquired by satellites became available to the public. In such data, many features and phenomena of geometric structure of man-made objects and natural environments become observable. In this paper, we discuss main considerations including geometric distortion and coregistration for efficient utilization of high resolution SAR images. And, various advanced technologies in SAR application fields are introduced.

• Proceedings of the KSRS Conference
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.254-257
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• 2007

This paper presents an examination of the spatial integration method for extracting the RCS of a trihedral corner reflector from SAR images for SAR external calibration. An exact external radiometric calibration technique is required for extracting an exact calibration constant. Therefore, we examine the accuracy of the spatial integration method, which is commonly used for the SAR external radiometric calibration. At first, an SAR image for a trihedral corner reflector is simulated with a high-resolution SAR impulse response with a known theoretical RCS of the reflector, and a background clutter image for the high resolution SAR system is also generated. Then, a SAR image in a high resolution is generated for a trihedral comer reflector located on a background clutter by superposition of the two SAR images. The radar cross section of a trihedral corner reflector in the SAR image is retrieved by integrating the radar signals of the pixels adjacent to the reflector for various size of the integration area. By comparison of the measured RCS by the integration method and the theoretical RCS of the reflector, the effect of the size of the integration area on the extraction of the calibration constant is examined.

• KSCE Journal of Civil and Environmental Engineering Research
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• 제44권1호
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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.

• Journal of Korean Society for Geospatial Information Science
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• 제20권3호
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• pp.41-48
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• 2012

Using multi-sensor or multi-temporal high resolution satellite images together is essential for efficient applications in remote sensing area. The purpose of this paper is to estimate geometric difference of translations between high-resolution optical and SAR images automatically. The geometric and radiometric pre-processing steps were fulfilled to calculate the similarity between optical and SAR images by using Mutual Information method. The coarsest-level pyramid images of each sensor constructed by gaussian pyramid method were generated to estimate the initial translation difference of the x, y directions for calculation efficiency. The precise geometric difference of translations was able to be estimated by applying this method from coarsest-level pyramid image to original image in order. Yet even when considered only translation between optical and SAR images, the proposed method showed RMSE lower than 5m in all study sites.

• Korean Journal of Remote Sensing
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• 제31권3호
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• pp.227-244
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• 2015

Synthetic Aperture Radar is able to provide images of wide coverage in day, night, and all-weather conditions. Recently, as the SAR image resolution improves up to the sub-meter level, their applications are rapidly expanding accordingly. Especially there is a growing interest in the use of geographic information of high resolution SAR images and the change detection will be one of the most important technique for their applications. In this paper, an automatic threshold tracking and change detection algorithm is proposed applicable to high-resolution SAR images. To detect changes within SAR image, a reference image is generated using log-ratio operator and its amplitude distribution is estimated through K-S test. Assuming SAR image has a non-gaussian amplitude distribution, a generalized thresholding technique is applied using Kittler and Illingworth minimum-error estimation. Also, MoLC parametric estimation method is adopted to improve the algorithm performance on rough ground target. The implemented algorithm is tested and verified on the simulated SAR raw data. Then, it is applied to the spaceborne high-resolution SAR images taken by Cosmo-Skymed and KOMPSAT-5 and the performances are analyzed and compared.

• Journal of Satellite, Information and Communications
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• 제12권1호
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• pp.6-12
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• 2017

Recently, the demand for SAR imaging is growing to monitor natural disasters or military sites to foresee topographic changes, where optical sensing is not easily available. High-resolution SAR images are useful in exploring topography and monitoring artificial land objects in all weather conditions. In this paper,high resolution SAR images acquired from KOMPSAT-5 are exploited for the applications of change detection and classification. In order to detect change areas, amplitude change detection (ACD) and coherence change detection (CCD) algorithms are employed and their performances are compared in practical applications. For enhanced performance, the potential of small scaled change detection is explored by combining multi-temporary SAR images. The k-means and SVM methods are applied for land classifications and their performances are compared by applying to the real spaceborne SAR images.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• 제30권1호
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• pp.75-86
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• 2012

Synthetic Aperture Radar(SAR) imaging system is independent of solar illumination and weather conditions; however, SAR image is difficult to interpret as compared with optical images. It has been increased interest in multi-sensor fusion technique which can improve the interpretability of $SAR^{\circ\circ}$ images by fusing the spectral information from multispectral(MS) image. In this paper, a multi-sensor fusion method based on high-frequency extraction process using Fast Fourier Transform(FFT) and outlier elimination process is proposed, which maintain the spectral content of the original MS image while retaining the spatial detail of the high-resolution SAR image. We used TerraSAR-X which is constructed on the same X-band SAR system as KOMPSAT-5 and KOMPSAT-2 MS image as the test data set to evaluate the proposed method. In order to evaluate the efficiency of the proposed method, the fusion result was compared visually and quantitatively with the result obtained using existing fusion algorithms. The evaluation results showed that the proposed image fusion method achieved successful results in the fusion of SAR and MS image compared with the existing fusion algorithms.

• Proceedings of the IEEK Conference
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• 대한전자공학회 2001년도 제14회 신호처리 합동 학술대회 논문집
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• pp.117-120
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• 2001

Synthetic aperture radar (SAR) is a promising active remote sensing technique to obtain large terrain information of the earth in all-weather conditions. SAR is useful in many applications, including terrain mapping and geographic information system (GIS), which use SAR display images. Usually, these applications need the enormous data storage because they deal with wide terrain images with high resolution. So, compression technique is a useful approach to deal with SAR display images with limited storage. Because there is some indispensable data loss through the conversion of a complex SAR image to a display image, some applications, which need high-resolution images, cannot tolerate more data loss during compression. Therefore, lossless compression is appropriate to these applications. In this paper, we propose a novel lossless compression technique for a SAR display image using one-step predictor and block arithmetic coding.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• 제20권2호
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• pp.183-192
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• 2009

SAR(Synthetic Aperture Radar) is an all-weather imaging radar and is widely used in military and civil application. Especially high-resolution SAR images are very important in military purpose because it can be used at target recognition application. LIG Nex1 developed a SAR system called NexSAR with bandwidth of 600 MHz and resolution of 30 cm to obtain technologies required for high-resolution SAR. To achieve 600 MHz bandwidth of waveform generator, two DDSs are used and its output signals are SSB modulated. And deramp technique is used to reduce the sampling rate of ADC at high resolution mode. NexSAR has stripmap and spotlight modes and its functionality and performances are evaluated through ground and flight tests.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• 제30권6_1호
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• pp.519-528
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• 2012

It was pointed out that the terrain distortion of SAR image is even worse than that of optical image although SAR imagery has the advantages of being independent of solar illumination and weather conditions. It is thus necessary to correct terrain distortion in SAR image for various application areas to integrate SAR and optical image information. There has to be a clear evaluation of terrain correction of high resolution SAR image according to the quality of DEM because the DEM of study site is generally used in the process of terrain correction. To achieve this issue, this paper compared the effects of quality of Digital Elevation Model(DEM) in the process of terrain correction of high resolution SAR images, using the DEM produced from 1:5000 topographic contour maps, LiDAR DEM, ASTER GDEM, SRTM DEM. We used TerraSAR-X and Cosmo-SkyMed, as the test data set, which are constructed on the same X-band SAR system as KOMPSAT-5. In order to evaluate quantitatively the correction results, we conducted comparative evaluation with the KOMPSAT-2 ortho image of the same region. The evaluation results showed that the DEM produced from 1:5000 topographic contour maps achieved successful results in the terrain correction of SAR image compared with the other DEM data, and the widely used SRTM DEM data in various applications was not suitable for the terrain correction of high resolution SAR images.