Automatic Generation of Digital Elevation Model Using Geo Eye-1 Stereo-pair Imagery

In this paper, we have generated a 5m Digital Elevation Model (DEM) from GeoEye-1 along-track stero pair satellite imagery. The Rational Polynomial Coefficients (RPCs) provided by vendors are biased using the Rational Function Model (RFM) to improve the geo-positional accuracy. The texture features and edge features are extracted to efficiently identify the conjugate points. Epipolar resampling is performed and Normalized Correlation Coefficient (NCC) is used as a template matching technique. The patch transformation using the slope and aspect analysis is performed to match the conjugate points and whose success rate is more than without using patch transformation. The points which satisfy the defined correlation factor are accepted for DEM construction. The RMSE at five different random points of generated DEM are calculated using Google earth data and found better than LPS eATE algorithm