• Title/Summary/Keyword: triangulation-based local transformation

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Image registration using outlier removal and triangulation-based local transformation (이상치 제거와 삼각망 기반의 지역 변환을 이용한 영상 등록)

  • Ye, Chul-Soo
    • Korean Journal of Remote Sensing
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    • v.30 no.6
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    • pp.787-795
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    • 2014
  • This paper presents an image registration using Triangulation-based Local Transformation (TLT) applied to the remaining matched points after elimination of the matched points with gross error. The corners extracted using geometric mean-based corner detector are matched using Pearson's correlation coefficient and then accepted as initial matched points only when they satisfy the Left-Right Consistency (LRC) check. We finally accept the remaining matched points whose RANdom SAmple Consensus (RANSAC)-based global transformation (RGT) errors are smaller than a predefined outlier threshold. After Delaunay triangulated irregular networks (TINs) are created using the final matched points on reference and sensed images, respectively, affine transformation is applied to every corresponding triangle and then all the inner pixels of the triangles on the sensed image are transformed to the reference image coordinate. The proposed algorithm was tested using KOMPSAT-2 images and the results showed higher image registration accuracy than the RANSAC-based global transformation.

A study on the Accuracy Analysis of the World Geodetic System Transformation for GIS Base Map and Database (GIS 기본도 및 DB의 세계측지계 좌표변환 정확도 분석에 관한 연구)

  • Cho, Jae-Kwan;Choi, Yun-Soo;Kwon, Jay-Hyoun;Lee, Bo-Mi
    • Journal of Korean Society for Geospatial Information Science
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    • v.16 no.3
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    • pp.79-85
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    • 2008
  • This study aims to derive a practical coordinate transformation method for the existing geographic information database. After analyzing the status and problems of existing 1/1,000 digital base map and GIS application database, the transformation parameters are estimated and the accuracy of the transformation is determined based on the transformed coordinates. We analyzed the accuracy of a transformation using the published national transformation coefficients as well as the estimated local transformation coefficients using national and urban control points in a study area. In addition, the 1/1,000 digital base map from aerial triangulation is compared with respect to the coordinates of urban control points. Based on the comparison, the biases on the national control points which were used at the time of digital map generation was analyzed. Then, the accuracy of transformed coordinates based on the world geodetic system using local transformation coefficients estimated from urban control points are determined. We also analyzed the transformation accuracy of underground infrastructure database using the same transformation method as the case of 1/1,000 digital base map. Through this study, it was found that the estimation of transformation coefficients by Molodensky-Badekas using urban control points was suitable for a local government. Furthermore, it was obvious that the accuracy of a 2-dimensional affine transformation was comparable to that of 7 parameter transformation for a local area. Applying the coordinate transformation and bias correction, we could transform GIS application database which was built by an offset surveying based on digital base map within the transformation accuracy of 10 cm. Therefore, it was judged that there will not be a big problem on the transformation of the GIS DB to the world geodetic system.

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A Study on the Transformation of Two Dimensional Geodetic Coordinates between Bessel and WGS84 Ellipsoids by UTM Projection (UTM투영에 의한 Bessel과 WGS84 타원체간의 2차원 측지좌표변환 연구)

  • 이용창;강준묵
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.16 no.2
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    • pp.149-158
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    • 1998
  • The aim of this paper is to propose the technique of the two dimensional geodetic coordinates conversion between WGS84 and Bessel spheroids by the two-dimensional affine transformation modeling based on the UTM plane coordinates without the local geoid model which is essential to three dimensional coordinates conversion. Area of approximately $25\times{11}$ square km in the city of Inchon was selected as the test area. The transformation parameters were determined using the eleven triangulation control points in test area. And then, those paraneters were applied to the fifteen cadastral control points which selected as checking points for precision checking of transformation parameters. The average and standard deviations of the absolute values of the conversion residuals of checking points in latitude/longitude and N/E(UTM) and/or x/y(TM) are $\pm0.006"$$\pm0.013"$ and $\pm{17cm/}\pm{30cm}$ respectively. Also, coefficients for 7-parameters, 3-parameters and UTM model transformation computed according as sizes of transformed area, and then the transformed characteristics of checking points according to transformation methods analyzed synthetically.hetically.

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Extraction of water body in before and after images of flood using Mahalanobis distance-based spectral analysis

  • Ye, Chul-Soo
    • Korean Journal of Remote Sensing
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    • v.31 no.4
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    • pp.293-302
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    • 2015
  • Water body extraction is significant for flood disaster monitoring using satellite imagery. Conventional methods have focused on finding an index, which highlights water body and suppresses non-water body such as vegetation or soil area. The Normalized Difference Water Index (NDWI) is typically used to extract water body from satellite images. The drawback of NDWI, however, is that some man-made objects in built-up areas have NDWI values similar to water body. The objective of this paper is to propose a new method that could extract correctly water body with built-up areas in before and after images of flood. We first create a two-element feature vector consisting of NDWI and a Near InfRared band (NIR) and then select a training site on water body area. After computing the mean vector and the covariance matrix of the training site, we classify each pixel into water body based on Mahalanobis distance. We also register before and after images of flood using outlier removal and triangulation-based local transformation. We finally create a change map by combining the before-flooding water body and after-flooding water body. The experimental results show that the overall accuracy and Kappa coefficient of the proposed method were 97.25% and 94.14%, respectively, while those of the NDWI method were 89.5% and 69.6%, respectively.