• 한국전자파학회논문지
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• 제29권6호
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• pp.464-472
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• 2018

최근 위성 SAR(Synthetic Aperture Radar) 시스템의 개발은 광역 관측을 수행하는 동시에, 고해상도 영상을 확보하는 방향으로 확장되고 있다. 일반적인 위성 SAR 시스템에서는 광역의 고해상도 영상을 획득하는 과정에서 방위 및 거리방향의 모호성 문제가 유발되어 영상 품질의 저하가 발생한다. 다중 입출력 장치를 사용하는 MIMO(Multiple Input Multiple Output) SAR 기술은 상호 상관성이 낮은 파형군을 적용하여 관측폭을 확장하면서도 영상 품질을 유지하는 기법으로 제안되고 있다. 본 논문에서는 상호 직교 특성을 갖는 다중 잡음 OFDM(Orthogonal Frequency Division Multiplex) 파형을 설계하고, 다중 파형 모드에서의 영상 품질 분석을 수행하여 광역 고해상도 SAR 모드에 적용 가능성을 제시한다.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2004년도 춘계학술발표회논문집
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• pp.337-343
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• 2004

Spatial information could be obtained from spaceborne high resolution optical and synthetic aperture radar(SAR) images. However, some satellite images do not provide physical sensor information instead, rational polynomial coefficients(RPC) are available. The objectives of this study are: (1) 3-dimensional ground coordinates were computed by applying rational function model(RFM) with the RPC for the stereo pair of Ikonos images and their accuracy was evaluated. (2) Interferometric SAR(InSAR) was applied to JERS-1 images to generate DEM and its accuracy was analysis. (3) Quality of the DEM generated automatically also analyzed for different types of terrain in the study site. The overall accuracy was evaluated by comparing with GPS surveying data. The height offset in the RPC was corrected by estimating bias. In consequence, the accuracy was improved. Accuracy of the DEMs generated from InSAR with different selection of GCP was analyzed. In case of the Ikonos images, the results show that the overall RMSE was 0.23327", 0.l1625" and 13.70m in latitude, longitude and height, respectively. The height accuracy was improved after correcting the height offset in the RPC. i.e., RMSE of the height was 1.02m. As for the SAR image, RMSE of the height was 10.50m with optimal selection of GCP. For the different terrain types, the RMSE of the height for urban, forest and flat area was 23.65m, 8.54m, 0.99m, respectively for Ikonos image while the corresponding RMSE was 13.82m, 18.34m, 10.88m, respectively lot SAR image.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.667-670
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• 2005

Ground control points(GCPs) can be extracted from SAR data given precise orbit for DTM generation using optic images and other SAR data. In this study, we extract GCPs from ERS SAR data and SRTM DEM. Although it is very difficult to identify GCPs in ERS SAR image, the geometry of optic image and other SAR data are able to be corrected and more precise DTM can be constructed from stereo optic images. Twenty GCPs were obtained from the ERS SAR data with precise Delft orbit information. After the correction was applied, the mean values of planimetric distance errors of the GCPs were 3.7m, 12.1 and -0.8m with standard deviations of 19.9m, 18.1, and 7.8m in geocentric X, Y, and Z coordinates, respectively. The geometries of SPOT stereo pair were corrected by 13 GCPs, and r.m.s. errors were 405m, 705m and 8.6m in northing, easting and height direction, respectively. And the geometries of RADARS AT stereo pair were corrected by 12 GCPs, and r.m.s. errors were 804m, 7.9m and 6.9m in northing, easting and height direction, respectively. DTMs, through a method of area based matching with pyramid images, were generated by SPOT stereo images and RADARS AT stereo images. Comparison between points of the obtained DTMs and points estimated from a national 1 :5,000 digital map was performed. For DTM by SPOT stereo images, the mean values of distance errors in northing, easting and height direction were respectively -7.6m, 9.6m and -3.1m with standard deviations of 9.1m, 12.0m and 9.1m. For DTM by RADARSAT stereo images, the mean values of distance errors in northing, easting and height direction were respectively -7.6m, 9.6m and -3.1m with standard deviations of 9.1m, 12.0m and 9.1m. These results met the accuracy of DTED level 2

• 한국군사과학기술학회지
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• 제24권5호
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• pp.475-481
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• 2021

The on-board processor of satellite Synthetic Aperture Radar(SAR) digitizes the back-scattered echoes and transmits them to the ground. As satellite SAR image of various operating conditions including broadband and high resolution is required, an enormous amount of SAR data is generated. Decimation filter is used for data compression to improve the transmission efficiency of these data. Decimation filter is implemented with the FIR(Finite Impulse Response) filter and here, the decimation ratio and tap length are constrained by resource requirements of FPGA used for implementation. This paper suggests to use a non-integer ratio decimation filter in order to optimize the data transmission efficiency. Also, it proposes a filter design method that remarkably reduces the resource constraints of the FPGA in-use via applying a polyphase filter structure. The required resources for implementing the proposed filter is analysed in this paper.

• 한국멀티미디어학회논문지
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• 제25권7호
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• pp.895-902
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• 2022

Building segmentation using satellite imagery such as EO (Electro-Optical) and SAR (Synthetic-Aperture Radar) images are widely used due to their various uses. EO images have the advantage of having color information, and they are noise-free. In contrast, SAR images can identify the physical characteristics and geometrical information that the EO image cannot capture. This paper proposes a learning framework for efficient building segmentation that consists of a teacher-student-based privileged knowledge distillation and deformable convolution block. The teacher network utilizes EO and SAR images simultaneously to produce richer features and provide them to the student network, while the student network only uses EO images. To do this, we present objective functions that consist of Kullback-Leibler divergence loss and knowledge distillation loss. Furthermore, we introduce deformable convolution to avoid pixel-level noise and efficiently capture hard samples such as small and thin buildings at the global level. Experimental result shows that our method outperforms other methods and efficiently captures complex samples such as a small or narrow building. Moreover, Since our method can be applied to various methods.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2009년도 추계학술대회
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• pp.73-74
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• 2009

This study attempts to establish a system extracting and monitoring cultural grounds of seaweeds (lavers, brown seaweeds and seaweed fulvescens) and abalone on the basis of both KOMPSAT-2 and Terrasar-X data. The study areas are located in the northwest and southwest coast of South Korea, famous for coastal cultural grounds. The northwest site is in a high tidal range area (on the average, 6.1 m in Asan Bay) and has laver cultural grounds for the most. An semi-automatic detection system of laver facilities is described and assessed for spaceborne optic images. On the other hand, the southwest cost is most famous for seaweeds. Aquaculture facilities, which cover extensive portions of this area, can be subdivided into three major groups: brown seaweeds, capsosiphon fulvescens and abalone farms. The study is based on interpretation of optic and SAR satellite data and a detailed image analysis procedure is described here. On May 25 and June 2, 2008 the TerraSAR-X radar satellite took some images of the area. SAR data are unique for mapping those farms. In case of abalone farms, the backscatters from surrounding dykes allows for recognition and separation of abalone ponds from all other water-covered surfaces. But identification of seaweeds such as laver, brown seaweeds and seaweed fulvescens depends on the dampening effect due to the presence of the facilities and is a complex task because objects that resemble seaweeds frequently occur, particularly in low wind or tidal conditions. Lastly, fusion of SAR and optic spatial images is tested to enhance the detection of aquaculture facilities by using the panchromatic image with spatial resolution 1 meter and the corresponding multi-spectral, with spatial resolution 4 meters and 4 spectrum bands, from KOMPSAT-2. The mapping accuracy achieved for farms will be estimated and discussed after field verification of preliminary results.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.111-114
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• 2004

Object-based segmentation is the first essential step for image processing applications. Recently, SAR (Synthetic Aperture Radar) segmentation techniques have been developed, however not enough to preserve the significant information contained in the small regions of the images. The proposed method is to partition an SAR image into homogeneous regions by using a fuzzy hit-or-miss operator with an inherent spatial transformation, which endows to preserve the small regions. In our algorithm, an iterative segmentation technique is formulated as a consequential process. Then, each time in iterating, hypothesis testing is used to evaluate the quality of the segmented regions with a homogeneity index. The segmentation algorithm is unsupervised and employed few parameters, most of which can be calculated from the input data. This comparative study indicates that the new iterative segmentation algorithm provides acceptable results as seen in the tested examples of satellite images.

• 대한토목학회논문집
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• 제32권1D호
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• pp.89-94
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• 2012

범용센서모델의 한 종류인 비례다항식 모델(RFM: Rational Function Model)은 광학영상의 센서모델링분야에서 활발히 활용되고 있으나 SAR영상에 대한 적용은 미진한 실정이다. 본 연구에서는 스테레오 TerraSAR-X영상을 대상으로 RF 모델링을 적용하여 적용방법의 타당성과 효율성에 대해 분석하였다. 또한 본 연구성과의 DSM(Digital Surface Model)과 기존 상용 소프트웨어에서 생성된 DSM을 다양한 측면에서 비교 분석하였다. 그 결과 RF 모델링 기법이 SAR영상의 적용 시에도 매우 효과적이며 실용적으로 적용 가능함을 알 수 있었다.

• 대한공간정보학회지
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• 제20권3호
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• pp.41-48
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• 2012

고해상도 위성영상을 공간정보 분야에 효과적으로 활용하기 위해서는 다중센서와 다시기 영상 데이터를 공간분석에 함께 사용하여 이들 데이터의 장점을 최대한 활용하는 것이 중요하다. 본 연구에서는 고해상도의 다중센서자료를 동시에 활용하기 위해, 영상 간 존재하는 변위량을 자동으로 추정하여 다중센서 영상 간 기하보정을 수행하는 새로운 영상정합기법을 개발하였다. 영상의 취득 방식과 방사적 특성이 다른 광학영상과 SAR 영상 간의 유사도를 효과적으로 계산하기 위하여 기하적, 방사적 전처리 과정을 수행하였고, 두 영상 간 변위량 측정은 상호정보기법을 통해 계산하였다. 또한, 변위량 측정방식의 계산 효율과 정확도 향상을 위하여 영상 피라미드 방식을 적용하여 상위 피라미드 영상부터 차례로 x, y 방향에 대한 변위량을 최적화기법을 통해 추정하였다. 이러한 과정을 피라미드의 최하부인 원영상에까지 반복적으로 수행함으로써 두 영상 간 정밀한 변위량을 추정하였으며, 수동으로 추출된 검사점을 통해 제안기법에 대한 정확도 평가를 수행한 결과, 영상간 변위량에 대한 고려만으로도 약 5m 이내 (RMSE)의 기하보정 정확도를 도출할 수 있었다.

• 대한토목학회논문집
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• 제34권5호
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• pp.1639-1644
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• 2014

SAR 센서는 마이크로파를 이용한 능동센서로 기상조건에 상관없이 영상을 취득할 수 있다는 장점이 있어, 국토관리 및 재해 모니터링 등에 활발히 활용되고 있다. 주기적으로 취득되는 SAR 영상을 효과적으로 활용하기 위해서는 자동화된 영상 정합기법이 필요하지만 영상의 촬영 시간 및 기하에 따라 다른 양상의 기하조건을 가진 취득됨에 따라 충분한 정합 정확도를 기대하기 어렵다. 이에 본 연구에서는 기울기 속성을 추가한 MI (Mutual Information) 기법과 FMT (Fourier-Mellin Transform)기법, SIFT (Scale-Invariant Feature Transform) 기법을 임의의 변위와 회전 공차를 적용하고, 해상도를 변화시킨 TerraSAR-X 영상에 적용하여 그 결과를 비교하였다. 비교 결과, MI 기법의 경우엔 서로 상이한 기하에서 촬영된 영상에 적용하였을 때에도 일정 크기의 영상소가 다수 분포할 경우 0~2 픽셀 수준의 정확도를 지닐 수 있는 반면, FMT 기법의 경우에는 같은 사물에 대해서도 그 영상소 값이 서로 상이하여 정합 오차가 수십에서 수백 픽셀로 나타났다. 또한 SIFT 기법의 경우에도 영상 정합을 위한 공액점의 정확도가 0~17 % 수준으로 매우 낮아 서로 상이한 기하조건으로 취득된 SAR 영상에 적용이 어려울 것으로 나타났다.