Research for Automatic Generation and Update of DEM/Ortho-image from High Resolution Satellite Images

The main objective of this research is automatic generation of more accurate DEM/ortho-image and, by extension, to update existing DEMs and ortho-images database automatically by using high resolution satellite images. In the first part, we tested the possibility of automatic GCP and tie-point generation for DEMs and ortho-images generation. We extract Ground Control Points (GCPs) automatically from high resolution satellite image by using existing ortho-images and existing DEMs. In second part, we tested whether high resolution images can be used to update existing DEMs and ortho-images. For this, we performed automatic generation of DEMs/ortho-images by using true GCPs obtained by GPS surveying. For testing the method proposed, we used IKONOS, SPOT 5, QuickBird, Kompsat-2 high resolution satellite images. Assessment for results supports that automatic generation of DEMs/ortho-images was performed successfully. We generated a DEM from IKONOS images fully automatically by using GCPs generated from existing DEMs and ortho-images. Newly updated DEM was compared with existing data. Updated DEM shows more detailed surface, and the result of validation shows that the accuracy is similar with that of existing DEMs/ortho-images.

[1]  Taejung Kim,et al.  A Study on the Epipolarity of Linear Pushbroom Images , 2000 .

[2]  Rajiv Gupta,et al.  Linear Pushbroom Cameras , 1994, ECCV.

[3]  A. Bouillon,et al.  SPOT 5 HRS geometric performances: Using block adjustment as a key issue to improve quality of DEM generation , 2006 .

[4]  Taejung Kim,et al.  Automated urban area building extraction from high resolution stereo imagery , 1996, Image Vis. Comput..

[5]  Peter Reinartz,et al.  Accuracy analysis for DSM and orthoimages derived from SPOT HRS stereo data using direct georeferencing , 2006 .

[6]  Thierry Toutin,et al.  Comparison of stereo-extracted DTM from different high-resolution sensors: SPOT-5, EROS-a, IKONOS-II, and QuickBird , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[7]  Armin Gruen,et al.  SPOT-5/HRS STEREO IMAGES ORIENTATION AND AUTOMATED DSM GENERATION , 2004 .

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

[9]  Jorge Stolfi,et al.  Outlier rejection in high-dimensional deformable models , 2007, Image Vis. Comput..

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

[11]  Ian Dowman,et al.  Comparison of two physical sensor models for satellite images: Position–Rotation model and Orbit–Attitude model , 2006 .

[12]  T. Toutin.  Generation of DSMs from SPOT-5 in-track HRS and across-track HRG stereo data using spatiotriangulation and autocalibration , 2006 .

[13]  Heung-Kyu Lee,et al.  Extraction of digital elevation models from satellite stereo images through stereo matching based on epipolarity and scene geometry , 2003, Image Vis. Comput..