• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
• /
• 2003.04a
• /
• pp.354-362
• /
• 2003

위성영상으로부터 위치자료가 포함된 지리 및 지형정보를 얻기 위해서는 영상획득순간의 센서 위치 및 자세와 지상좌표간의 관계를 해석하여야 한다. 위성영상에 대한 수학적 모형화를 위해서 먼저 입체영상에서 지상기준점(Ground Control Point: GCP)을 선정하고, 선정된 지상기준점에 대한 지상좌표 및 대상영상에 대한 영상좌표 관측작업을 수행한다. 본 연구에서는 지상기준점 데이터베이스에 포함된 정보들을 이용하여 관측대상 입체영상 3차원 모형화에 필요한 지상기준점의 영상좌표를 자동으로 추출할 수 있는 기법을 개발하였다. 관측정밀도는 수작업으로 관측한 값과 자동계산된 영상좌표의 결과를 비교 분석하여 평가하였으며, SPOT위성영상의 3차원 모형화에 적용하여 정확도를 평가하므로써 유사한 해상도의영상을 활용하는 3차원 모형화 과정에서 지상기준점의 영상좌표 관측을 자동화 할 수 있음을 입증하였다.

• Proceedings of the Korea Multimedia Society Conference
• /
• 2004.05a
• /
• pp.187-190
• /
• 2004

본 논문에서는 영상을 자동적으로 객체와 비객체 영상으로 분류하는 방법을 제안한다. 객체 영상은 객체를 포함하는 영상이다. 객체는 영상의 중심 부근에 위치하고 주변 영역과는 상이한 칼라 분포를 가지는 영역들로 정의한다 영상 분류를 위해 객체의 특징에 기반하여 세 가지 기준을 정의한다. 첫 번째 기준인 중심 영역의 특이성은 중심영역과 주변 영역간의 칼라 분포의 차이를 통해 계산된다. 두 번째 기준은 영상 내의 특이 픽셀의 분산이다 특이 픽셀은 영상의 주변영역보다 중심 부근에서 더욱 빈번하게 나타나는 상호 인접한 픽셀들의 칼라 쌍에 의해 정의된다. 마지막 기준은 객체의 핵심 영역 경계에서의 경계 강도이다. 영상을 분류하기 위해서 신경 회로망 학습을 통해서 세 가지 기준들을 통합하도록 한다. 900개의 영상들에 대해 실헝한 결과 84.2%의 분류 정확도를 얻었다.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.27 no.3A
• /
• pp.249-257
• /
• 2002

본 논문에서는 스테레오/다시점 영상을 효율적으로 압축할 수 있는 차 영상 부호화 방법을 제안한다. 예측된 영상과 원 영상의 차이 정보를 보다 효율적으로 전송하기 위하여 DCT를 기반으로 차 영상 부호화를 하게 되는데 DCT 계수들의 방향성을 이용하여 양자화 및 스캔 방법을 각 블록의 특성에 따라 다르게 적용하였다. 특히 다시점 영상의 부호화는 첫 번째 시점 영상을 기준 영상으로 정하여 나머지 시점 영상을 기준 영상으로부터 변이를 추정하여 복원하는 방식과 다시점 영상 중 가려진 영역의 비율을 고려하여 가려진 영역이 상대적으로 제일 적은 영상을 기준 영상으로 설정하여 나머지 영상을 변이 추정하여 복원하는 방법으로 나누어 실험하였다. 실험 결과 모든 압축률에 대하여 제안 방식이 기존의 차 영상 부호화 방법보다 우수함을 확인하였고, 가려진 영역의 상대적인 비율을 고려하여 다시점 영상을 부호화한 제안 방식이 기존의 방식 및 첫 번째 시점을 기준 영상으로 설정하여 부호화한 제안 방식보다 우수함을 확인하였다.

• Progress in Medical Physics
• /
• v.9 no.1
• /
• pp.47-53
• /
• 1998

Nuclear Medicine Images have comparatively poor spatial resolution, making it difficult to relate the functional information which they contain to precise anatomical structures. Anatomical structures useful in the interpretation of SPECT /PET Images were radiolabelled. PET/SPECT Images Provide functional information, whereas MRI mainly demonstrate morphology and anatomical. Fusion or Image Registration improves the information obtained by correlating images from various modalities. Brain Scan were studied on one or more occations using MRI and SPECT. The data were aligned using a point pair methods and surface matching. SPECT and MR Images was tested using a three dimensional water fillable Hoffman Brain Phantom with small marker and PET and MR Image was tested using a patient data. Registration of SPECT and MR Images is feasible and allows more accurate anatomic assessment of sites of abnormal uptake in radiolabeled studies. Point based registration was accurate and easily implemented three dimensional registration of multimodality data set for fusion of clinical anatomic and functional imaging modalities. Accuracy of a surface matching algorithm and homologous feature pair matching for three dimensional image registration of Single Photon Emission Computed Tomography Emission Computed Tomography (SPECT), Positron Emission Tomography (PET) and Magnetic Resonance Images(MRD was tested using a three dimensional water fill able brain phantom and Patients data. Transformation parameter for translation and scaling were determined by homologous feature point pair to match each SPECT and PET scan with MR images.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.16 no.7
• /
• pp.1477-1486
• /
• 2012

In this paper, we propose Multi-view CGH Making System using method of generation of virtual view-point depth image. We acquire reliable depth image using TOF depth camera. We extract parameters of reference-view cameras. Once the position of camera of virtual view-point is defined, select optimal reference-view cameras considering position of it and distance between it and virtual view-point camera. Setting a reference-view camera whose position is reverse of primary reference-view camera as sub reference-view, we generate depth image of virtual view-point. And we compensate occlusion boundaries of virtual view-point depth image using depth image of sub reference-view. In this step, remaining hole boundaries are compensated with minimum values of neighborhood. And then, we generate final depth image of virtual view-point. Finally, using result of depth image from these steps, we generate CGH. The experimental results show that the proposed algorithm performs much better than conventional algorithms.

• 한국지형공간정보학회:학술대회논문집
• /
• 2004.10a
• /
• pp.33-37
• /
• 2004

고해상 입체 위성영상 엄밀 모델링(Rigorous Modeling)을 구현하고, 이를 기반으로 각 입체시 영상을 제작하여 3차원 정확도 평가를 수행하였다. 본 연구 지역으로 진주지역의 SPOTS 입체영상을 이용하였으며, 각 영상별 기준점 자료는 1/5000 수치지도를 이용하여 입체영상의 중복영역 내에 균등하게 지상기준점 40점을 추출하였다. 추출된 점을 각각 기준점과 검사점으로 구분하여 엄밀 모델링의 정확도를 분석하였다. 또한, 입체시 제작시에 기준점으로 사용된 지상좌표와 이에 대응하는 영상점을 이용하여 입체시 영상을 제작하였다. 제작된 입체시 영상에서 동일점을 획득하기 위해 영상 매칭 및 수치해석도화기(Helava System)를 이용하여 정확한 영상점을 획득하여 3차원 좌표를 계산하여 정확도 평가를 수행하였다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.21 no.1
• /
• pp.61-69
• /
• 2003

There is various kinds cause that influence to created DEM and orthoimage using stereo satellite images. Specialty, research about effect that GCP number gives to accuracy of DEM, orthoimage and modeling may have to be gone ahead. Therefore, this research increases GCP number by 5 to 30 and created each modeling, DEM and orthoimage using SPOT panchromatic images that resolution is 10m by digital image processing method. Accuracy assessment did by orthoimage using 20 check point. As a result, GCP number between 10∼30 modeling RMSE is 1 pixel low appear. Horizontal·vertical error that use orthoimage looked tendency that decrease GCP number increases, and confirmed by the most economical in GCP number 10∼15. Also, analyze correlation of GCP number and orthoimage position accuracy and presented improvement plan and research task hereafter.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.26 no.4
• /
• pp.423-431
• /
• 2008

The control surveying which aims at identifying the coordinate system of satellite images with that of ground is a repeatedly performed essential process to produce digital ortho - photos and it acts as the main factor to increase the production cost of the photos by duplicated budgets and redundant works when executing the projects for acquiring basic geographical information from high density satellite images. During the experimentation, an application system was established for producing a stereo image chip by the analysis of DPPDB file structure, the stereo image chip was produced with SPOT and IKONOS images, the analysis of 3D modeling accuracy was performed to secure the required accuracy and to present the optimal number and deployment of the control points, and a 3D modeling was performed for new SPOT images and lastly, 3D ground coordinates were extracted by the observation of the same points through the overlapping with the new images. As the results of the research, it is proved that the stereo image chip can be used as the ground controls through the accuracy analysis between the coordinates of the images and the ground, close results were obtained between the coordinates by the ground survey and those by the 3D modeling using new images and the observation of the same points, positional changes were not found during observing the same points, and the research presented the methodology for improving the process of the control survey by showing the availability of the image controls on the stereo image chip instead of the ground controls.

• Journal of Korean Society for Geospatial Information Science
• /
• v.15 no.4
• /
• pp.103-109
• /
• 2007

Ortho images and Digital Elevation Model (DEM) have been applied in various fields. It is necessary to acquire Ground Control Points (GCPs) for processing high resolution satellite images. However surveying GCPs require many time and expense. This study was performed to investigate whether GCPs automatically extracted from ortho images and DTED Level 2 can be applied to sensor modeling for high resolution satellite images. We analyzed the performance of the sensor model established by GCPs extracted automatically. We acquired GCPs by matching satellite image against ortho images. We included the height acquired from DTED Level 2 data in these GCPs. The spatial resolution of the DTED Level 2 data is about 30m. Absolution accuracy of this data is below 18m above MSL. The spatial resolution of ortho image is 1m. We established sensor model from IKONOS images using GCPs extracted automatically and generated DEMs from the images. The accuracy of sensor modeling is about $4{\sim}5$ pixel. We also established sensor models using GCPs acquired based on GPS surveying and generated DEMs. Two DEMs were similar. The RMSE of height from the DEM by automatic GCPs and DTED Level 2 is about 9 m. So we think that GCPs by DTED Level 2 and ortho image can use for IKONOS sensor modeling.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.4
• /
• pp.530-536
• /
• 2021

Since the LBP algorithm has the characteristic of local texture expression, it is possible to obtain completely different results depending on the extraction location and the size of the reference image and the sample image. In order to solve these shortcomings, in this paper, we first investigate the basic characteristics of LBP, make the size of the reference image (100×100) in order to include most of the characteristics in the image, and select a sample image (40×40) extracted from an arbitrary point. After finding the matching position in the LBP of the reference image by using the correlation test between the LBP of the reference image and the LBP of the sample image, a chi analysis method is used to find the reference image that most closely matches the sample image.