• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.475-491
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• 2021

With the recent increase in available high-resolution (< ~1 m) satellite SAR images, the demand for precise registration of SAR images is increasing in various fields including change detection. The registration between high-resolution SAR images acquired in different look angle is difficult due to speckle noise and geometric distortion caused by the characteristics of SAR images. In this study, registration is performed in two stages, coarse and fine, using the x-band SAR data imaged at staring spotlight mode of TerraSAR-X. For the coarse registration, a method combining the adaptive sampling method and SAR-SIFT (Scale Invariant Feature Transform) is applied, and three rigid methods (NCC: Normalized Cross Correlation, Phase Congruency-NCC, MI: Mutual Information) and one non-rigid (Gefolki: Geoscience extended Flow Optical Flow Lucas-Kanade Iterative), for the fine registration stage, was performed for performance comparison. The results were compared by using RMSE (Root Mean Square Error) and FSIM (Feature Similarity) index, and all rigid models showed poor results in all image combinations. It is confirmed that the rigid models have a large registration error in the rugged terrain area. As a result of applying the Gefolki algorithm, it was confirmed that the RMSE of Gefolki showed the best result as a 1~3 pixels, and the FSIM index also obtained a higher value than 0.02~0.03 compared to other rigid methods. It was confirmed that the mis-registration due to terrain effect could be sufficiently reduced by the Gefolki algorithm.

• Korean Journal of Remote Sensing
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• v.34 no.5
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• pp.739-747
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• 2018

Integration analysis of multi-sensor satellite images is becoming increasingly important. The first step in integration analysis is image registration between multi-sensor. SIFT (Scale Invariant Feature Transform) is a representative image registration method. However, optical image and SAR (Synthetic Aperture Radar) images are different from sensor attitude and radiation characteristics during acquisition, making it difficult to apply the conventional method, such as SIFT, because the radiometric characteristics between images are nonlinear. To overcome this limitation, we proposed a modified method that combines the SAR-SIFT method and shape descriptor vector DLSS(Dense Local Self-Similarity). We conducted an experiment using two pairs of Cosmo-SkyMed and KOMPSAT-2 images collected over Daejeon, Korea, an area with a high density of buildings. The proposed method extracted the correct matching points when compared to conventional methods, such as SIFT and SAR-SIFT. The method also gave quantitatively reasonable results for RMSE of 1.66m and 2.45m over the two pairs of images.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.11A
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• pp.1963-1970
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• 2001

It is essential design process to analyze processing method and set out top level HW configuration using main parameters before implementation of the SAR processor. This paper identifies the impact of the I/O and algorithm structure upon the parallel processing to be assessed and suggests the practical mapping method fur parallel processing to the SAR data. Also, simulation is performed to the E-SAR processor to examine the usefulness of the method, and the results are analyzed and discussed.

• Korean Journal of Remote Sensing
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• v.28 no.6
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• pp.671-682
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• 2012

Strong backscattering features from high-resolution Synthetic Aperture Rader (SAR) image provide useful information to analyze earth surface characteristics such as man-made objects in urban areas. The SAR image has, however, some limitations on description of detail information in urban areas compared to optical images. In this paper, we propose a new classification method using a fused SAR and Electro-Optical (EO) image, which provides more informative classification result than that of a single-sensor SAR image classification. The experimental results showed that the proposed method achieved successful results in combination of the SAR image classification and EO image characteristics.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.12
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• pp.1158-1166
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• 2013

SAR calculation method following the Mobi-Kids study protocol is analyzed and evaluation method of cumulative RF dose from mobile phones which have been used by a subject of case and control groups is proposed. An SAR database is built by calculating SAR distributions in 4 head models at different ages for representative phone models with the same conducted power. To obtain SAR distribution in a subject's head for a specific commercial phone which had/have been used by him/her, an SAR correction factor using SAR compliance test results is determined. Cumulative dose is calculated by considering mobile phone characteristics and use pattern such as call time and laterality(right and left).

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.7
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• pp.580-583
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• 2017

To compensate the degraded SAR image due to the residual errors and the spatial variant errors remaining after the motion compensation in the airborne SAR, we have introduced the autofocus method based on the partition processing. Thus, after we perform the spatial partition for the spotlight SAR data and the time partition for the stripmap SAR data, we reconstruct the subpatch images for the partitioned data. Then, we perform the local autofocus with the suitability analysis process for the phase errors estimated by the autofocus. Moreover, if the estimated phase errors are not properly compensated for the subpatch images, we perform the phase compensation method with the weight to the estimated phase error close to the degraded subpatch image to increase the SAR image quality.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.2
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• pp.171-182
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• 2022

InSAR (Interferometry SAR) technique is a technique that uses complex data to obtain phase difference information from two or more SAR image data, and enables high-resolution image extraction, surface change detection, elevation measurement, and glacial change observation. In many countries, research on the InSAR technique is being conducted in various fields of study such as volcanic activity detection, glacier observation in Antarctica, and ground subsidence analysis. In this study, a case of large ground settlement due to groundwater level drawdown during tunnelling was introduced, and ground settlement analyses using InSAR technique and numerical analysis method were compared. The maximum settlement and influence radius estimated by the InSAR technique and numerical method were found to be quite similar, which confirms the reliability of the InSAR technique. Through this case study, it was found that the InSAR technique reliable to use for estimating ground settlement and can be used as a key technology to identify the long-term ground settlement history in the absence of measurement data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.5
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• pp.1639-1644
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• 2014

SAR satellite can acquire clear imagery regardless of weather and the images are widely used for land management, natural hazard monitoring and many other applications. Automatic image matching technique is necessary for management of a huge amount of SAR data. Nevertheless, it is difficult to assure the accuracy of image matching due to the difference of image-capturing attitude and time. In this paper, we compared performances of MI method, FMT method and SIFT method by applying arbitrary displacement and rotation to TerraSAR-X images and changing resolution of the images. As a result, when the features having specific intensity were distributed well in SAR imagery, MI method could assure 0~2 pixels accuracy even if the images were captured in different geometry. But the accuracy of FMT method was significantly poor for the images having different spatial resolutions and the error was represented by tens or hundreds pixels. Moreover, the ratio of corresponding matching points for SIFT method was only 0~17% and it was difficult for SIFT method to apply to SAR images captured in different geometry.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.522-525
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• 2004

Interferometry SAR (InSAR) is a technique to generate topographic map from complex data pairs observed by antennas at different locations. However, to obtain topographic information using InSAR is difficult task because it requires series of complicated process including phase unwrapping and precise recovery of the SAR geometry. Especially, accuracy of the DEM (Digital Elevation Model) produced by repeat pass single SAR pair could be influenced by atmospheric effect. Recently, a new InSAR technique to improve accuracy of DEM has been introduced that utilizes low resolution DEM with a number of SAR image pairs. The coarse DEM plays an important role in reducing phase unwrapping error caused by layover and satellite orbit error. In this study, we implemented DInSAR (Differential InSAR) method which combines low resolution DEMs and ERS tandem pair images. GTOPO30 DEM with 1km resolution, SRTM-3 DEM with 100m resolution, and DEM with 10m resolution derived from 1:25,000 digital vector map were used to investigate feasibility of DInSAR. The accuracy of the DEMs generated both by InSAR and DInSAR was evaluated.

• Journal of Biomedical Engineering Research
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• v.18 no.3
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• pp.261-266
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• 1997

Nonevasive multifrequency microwave radiometry using coaxial waveguide antenna has been investigated for a homogeneous and four layer human body model. The coupling between coaxial waveguide antenna and a biological object was analyzed by use of the finite-difference time-domain(FDTD) method to obtain the absorbed power patterns in the media. The object studied in this paper was a homogeneous and four-layered lossy medium. The specific absorption rates(SAR) distribution which was corresponding to the temperature distribution was calculated in each region by use of the steady-state response in FDTD method. The SAR pattern of 1.2GHz was compared with that of 1.8GHz.