• Title/Summary/Keyword: 고해상도 영상정보

Search Result 670, Processing Time 0.031 seconds

Analysis of Tidal Channel Variations Using High Spatial Resolution Multispectral Satellite Image in Sihwa Reclaimed Land, South Korea (고해상도 다분광 인공위성영상자료 기반 시화 간척지 갯골 변화 양상 분석)

  • Jeong, Yongsik;Lee, Kwang-Jae;Chae, Tae-Byeong;Yu, Jaehyung
    • Korean Journal of Remote Sensing
    • /
    • v.36 no.6_2
    • /
    • pp.1605-1613
    • /
    • 2020
  • The tidal channel is a coastal sedimentary terrain that plays the most important role in the formation and development of tidal flats, and is considered a very important index for understanding and distribution of tidal flat sedimentation/erosion terrain. The purpose of this study is to understand the changes in tidal channels by a period after the opening of the floodgate of the seawall in the reclaimed land of Sihwa Lake using KOMPSAT high-resolution multispectral satellite image data and to evaluate the applicability and efficiency of high-resolution satellite images. KOMPSAT 2 and 3 images were used for extraction of the tidal channels' lineaments in 2009, 2014, and 2019 and were applied to supervised classification method based on Principal Component Analysis (PCA), Artificial Neural Net (ANN), Matched Filtering (MF), and Spectral Angle Mapper (SAM) and band ratio techniques using Normalized Difference Water Index (NDWI) and MF/SAM. For verification, a numerical map of the National Geographic Information Service and Landsat 7 ETM+ image data were utilized. As a result, KOMPSAT data showed great agreement with the verification data compared to the Landsat 7 images for detecting a direction and distribution pattern of the tidal channels. However, it has been confirmed that there will be limitations in identifying the distribution of tidal channels' density and providing meaningful information related to the development of the sedimentary process. This research is expected to present the possibility of utilizing KOMPSAT image-based high-resolution remote exploration as a way of responding to domestic intertidal environmental issues, and to be used as basic research for providing multi-platform-image-based convergent thematic maps and topics.

차세대 영상보안 기술 동향

  • Jeon, Yong-Sung;Han, Jong-Wook;Cho, Hyun-Sook
    • Review of KIISC
    • /
    • v.20 no.3
    • /
    • pp.9-17
    • /
    • 2010
  • 본 논문에서는 현재 산업체뿐 만 아니라, 개인 생활에 많은 영향을 미치고 있는 영상보안 산업의 기술 현황을 살펴보고, IP 환경으로 진화함에 따른 차세대 영상보안시스템이 가져야할 요구사항과 이에 대한 국내외 기술개발 현황을 살펴보았다. 특히, 영상보안 기술의 발전 방향으로 예상되는 고해상도 네트워크 카메라, NVR, 그리고 차세대 영상보안을 선도할 스마트카메라 기술에 대해 분석하였다.

Extraction of 3D Building Information using Shadow Analysis from Single High Resolution Satellite Images (단일 고해상도 위성영상으로부터 그림자를 이용한 3차원 건물정보 추출)

  • Lee, Tae-Yoon;Lim, Young-Jae;Kim, Tae-Jung
    • Journal of Korean Society for Geospatial Information Science
    • /
    • v.14 no.2 s.36
    • /
    • pp.3-13
    • /
    • 2006
  • Extraction of man-made objects from high resolution satellite images has been studied by many researchers. In order to reconstruct accurate 3D building structures most of previous approaches assumed 3D information obtained by stereo analysis. For this, they need the process of sensor modeling, etc. We argue that a single image itself contains many clues of 3D information. The algorithm we propose projects virtual shadow on the image. When the shadow matches against the actual shadow, the height of a building can be determined. If the height of a building is determined, the algorithm draws vertical lines of sides of the building onto the building in the image. Then the roof boundary moves along vertical lines and the footprint of the building is extracted. The algorithm proposed can use the shadow cast onto the ground surface and onto facades of another building. This study compared the building heights determined by the algorithm proposed and those calculated by stereo analysis. As the results of verification, root mean square errors of building heights were about 1.5m.

  • PDF

Comparative Research of Image Classification and Image Segmentation Methods for Mapping Rural Roads Using a High-resolution Satellite Image (고해상도 위성영상을 이용한 농촌 도로 매핑을 위한 영상 분류 및 영상 분할 방법 비교에 관한 연구)

  • CHOUNG, Yun-Jae;GU, Bon-Yup
    • Journal of the Korean Association of Geographic Information Studies
    • /
    • v.24 no.3
    • /
    • pp.73-82
    • /
    • 2021
  • Rural roads are the significant infrastructure for developing and managing the rural areas, hence the utilization of the remote sensing datasets for managing the rural roads is necessary for expanding the rural transportation infrastructure and improving the life quality of the rural residents. In this research, the two different methods such as image classification and image segmentation were compared for mapping the rural road based on the given high-resolution satellite image acquired in the rural areas. In the image classification method, the deep learning with the multiple neural networks was employed to the given high-resolution satellite image for generating the object classification map, then the rural roads were mapped by extracting the road objects from the generated object classification map. In the image segmentation method, the multiresolution segmentation was employed to the same satellite image for generating the segment image, then the rural roads were mapped by merging the road objects located on the rural roads on the satellite image. We used the 100 checkpoints for assessing the accuracy of the two rural roads mapped by the different methods and drew the following conclusions. The image segmentation method had the better performance than the image classification method for mapping the rural roads using the give satellite image, because some of the rural roads mapped by the image classification method were not identified due to the miclassification errors occurred in the object classification map, while all of the rural roads mapped by the image segmentation method were identified. However some of the rural roads mapped by the image segmentation method also had the miclassfication errors due to some rural road segments including the non-rural road objects. In future research the object-oriented classification or the convolutional neural networks widely used for detecting the precise objects from the image sources would be used for improving the accuracy of the rural roads using the high-resolution satellite image.

Hierarchical Feature Based Block Motion Estimation for Ultrasound Image (초음파 영상을 위한 계층적 특징점 기반 블록 움직임 추출)

  • Shin, Seong-Chul;Kim, Baek-Sop;Bae, Moo-Ho
    • Proceedings of the Korean Information Science Society Conference
    • /
    • 2005.07b
    • /
    • pp.745-747
    • /
    • 2005
  • 본 논문은 연속 초음파 영상으로부터 모자이크 영상을 구하기 위한 특징점 기반 블록 움직임 추출 방법에서 정확도를 높이고 계산 시간을 줄이기 위해 다해상도(multi-resolution)영상을 이용한 계층적 특징점 기반 블록 움직임 추출 방법을 제시하였다. 초음파 영상에서의 Speckle 노이즈의 영향을 줄이기 위해 저해상도의 영상에서 특징점을 추출하고, 계산 시간을 줄이기 위해 저해상도 영상의 추정된 움직임을 고해상도 영상의 움직임 추정에 적용하여 탐색 범위를 줄였다. 그 결과 계산 시간을 개선하면서 모자이크 영상의 정확도를 높일 수 있었다.

  • PDF

스마트폰을 위한 동영상 압축 기술

  • Ho, Yo-Seong;Choe, Jeong-A
    • Information and Communications Magazine
    • /
    • v.29 no.4
    • /
    • pp.22-29
    • /
    • 2012
  • 스마트폰이 대중화되면서 이동통신 시장은 일대 혁신을 맞이했다. 최근 출시되는 스마트폰이 크고 선명한 화면과 빠른 프로세서를 잇따라 탑재하면서 고해상도 및 고품질 영상에 대한 사용자들의 수요가 급증하고 있다. 하지만 고해상도 및 고품질 영상은 데이터의 양이 방대하므로 실제 서비스 적용을 위해서는 데이터 통신 트래픽의 증가 및 저장 공간의 한계로 인한 문제를 해결해야 한다. 이에 따라 MPEG과 VCEG은 JCT-VC(joint collaborative team on video coding)를 설립하고 차세대 비디오 압축 표준인 HEVC(high efficiency video coding)의 국제 표준화 작업을 시작했다. 2010년 4월에 시작된 JCT-VC 회의는 최근 제 7차 회의까지 진행되었으며, 향후 2013년 1월까지 최종 국제 규격안(final draft international standard, FDIS)이 제정될 예정이다. 이 논문에서는 HEVC의 표준화 과정, 요구사항, 실험 영상 및 부호화 모드, 응용 분야, 최신 표준화 동향 등을 알아본다.

The optimized analysis zone districting using variogram in urban remote sensing (도시원격탐사에서 베리오그램을 이용한 최적의 분석범위 구역화)

  • Yoo, Hee-Young;Lee, Ki-Won;Kwon, Byung-Doo
    • Proceedings of the KSRS Conference
    • /
    • 2008.03a
    • /
    • pp.29-34
    • /
    • 2008
  • 최근에 객체의 경계가 분명하게 나타나는 고해상도 위성영상을 분석하는 연구가 활발히 이루어지고 있다. 고해상도 영상을 이용해 도시지역을 세분화하여 연구하려고 할 때 분석의 범위는 임의로 결정되는 경우가 많다. 사전정보가 충분하다면 임의로 결정하는 것이 가능하지만 그렇지 않을 경우 영상만을 이용해 연구 지역의 최적 분석범위를 결정하는 것은 쉽지 않다. 이 연구에서는 영상자료의 베리오그램을 작성하고 이론적 베리오그램의 상관거리를 통해 최적의 분석범위를 결정하고자 하였다. 베리오그램의 상관거리는 객체의 크기와 객체사이의 거리가 반영된 객관적인 수치이므로 사전자료가 없는 경우 효과적으로 기본 분석단위를 결정하는데 도움을 줄 수 있을 것으로 기대된다.

  • PDF

Regularized Adaptive High-resolution Image Reconstruction Considering Inaccurate Subpixel Registration (부정확한 부화소 단위의 위치 추정 오류에 적응적인 정규화된 고해상도 영상 재구성 연구)

  • Lee, Eun-Sil;Byun, Min;Kang, Moon-Gi
    • Journal of Broadcast Engineering
    • /
    • v.8 no.1
    • /
    • pp.19-29
    • /
    • 2003
  • The demand for high-resolution images is gradually increasing, whereas many imaging systems yield aliased and undersampled images during image acquisition. In this paper, we propose a high-resolution image reconstruction algorithm considering inaccurate subpixel registration. A regularized Iterative reconstruction algorithm is adopted to overcome the ill-posedness problem resulting from inaccurate subpixel registration. In particular, we use multichannel image reconstruction algorithms suitable for application with multiframe environments. Since the registration error in each low-resolution has a different pattern, the regularization parameters are determined adaptively for each channel. We propose a methods for estimating the regularization parameter automatically. The preposed algorithm are robust against the registration error noise. and they do not require any prior information about the original image or the registration error process. Experimental results indicate that the proposed algorithms outperform conventional approaches in terms of both objective measurements and visual evaluation.

Change Detection Using the IKONOS Satellite Images (IKONOS 위성영상을 이용한 변화 탐지)

  • Kang, Gil-Seon;Shin, Sang-Cheul;Cho, Kyu-Jon
    • Journal of Korean Society for Geospatial Information Science
    • /
    • v.11 no.2 s.25
    • /
    • pp.61-66
    • /
    • 2003
  • The change detection using the satellite imagery and airphotos has been carried out in the application of terrain mapping, environment, forestry, facility detection, etc. The low-spatial resolution data such as Landsat, NOAA satellite images is generally used for automatic change detection, while on the other hand the high-spatial resolution data is used for change detection by image interpretation. The research to integrate automatic method with manual change detection through the high-spatial resolution satellite image is performed. but the problem such as shadow, building 'lean' due to perspective geometry and precision geocorrection was found. In this paper we performed change detection using the IKONOS satellite images, and present the concerning problem.

  • PDF