Automatic Extraction Method of Control Point Based on Geospatial Web Service

This paper proposes an automatic extraction method of control point based on Geospatial Web Service. The proposed method consists of 3 steps. 1) The first step is to acquires reference data using the Geospatial Web Service. 2) The second step is to finds candidate control points in reference data and the target image by SURF algorithm. 3) By using RANSAC algorithm, the final step is to filters the correct matching points of candidate control points as final control points. By using the Geospatial Web Service, the proposed method increases operation convenience, and has the more extensible because of following the OGC Standard. The proposed method has been tested for SPOT-1, SPOT-5, IKONOS satellite images and has been used military standard data as reference data. The proposed method yielded a uniform accuracy under RMSE 5 pixel. The experimental results proved the capabilities of continuous improvement in accuracy depending on the resolution of target image, and showed the full potential of the proposed method for military purpose.

[1]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[2]  Yong-Woong Lee,et al.  Automatic Measuring of GCP's Image Coordinates using Control Point Patch and Auxiliary Points Matching , 2003 .

[3]  Marco Gianinetto,et al.  Automated Geometric Correction of High-resolution Pushbroom Satellite Data , 2008 .

[4]  Youkyung Han,et al.  AUTOMATIC REGISTRATION OF HIGH-RESOLUTION IMAGES IN URBAN AREAS USING LOCAL PROPERTIES OF FEATURES , 2011 .

[5]  Kamel Besbes,et al.  Automatic Remote-sensing Image Registration Using SURF , 2013 .

[6]  Chengqi Cheng,et al.  An automated registration of RS images based on SURF and piecewise linear transformation , 2010, 2010 The 2nd Conference on Environmental Science and Information Application Technology.

[7]  Luc Van Gool,et al.  SURF: Speeded Up Robust Features , 2006, ECCV.

[8]  Jan Flusser,et al.  Image registration methods: a survey , 2003, Image Vis. Comput..

[9]  Matthijs C. Dorst Distinctive Image Features from Scale-Invariant Keypoints , 2011 .

[10]  Aurélie Bouillon,et al.  USING A THREE DIMENSIONAL SPATIAL DATABASE TO ORTHORECTIFY AUTOMATICALLY REMOTE SENSING IMAGES , 2011 .

[11]  Taejung Kim,et al.  Automatic satellite image registration by combination of matching and random sample consensus , 2003, IEEE Trans. Geosci. Remote. Sens..

[12]  Luo Juan,et al.  A comparison of SIFT, PCA-SIFT and SURF , 2009 .

[13]  Z. Yi,et al.  Multi-spectral remote image registration based on SIFT , 2008 .