Open AccessOptimizing Orientation by GCP Refinement of Very High Resolution IKONOS Satellite Images
Author(s) -
Madhusudan Adhikari
Publication year - 2010
Publication title -
nepalese journal of geoinformatics/journal of geoinformatics nepal
Language(s) - English
Resource type - Journals
eISSN - 2717-5022
pISSN - 2676-1246
DOI - 10.3126/njg.v9i1.39688
Subject(s) - affine transformation , transformation (genetics) , constellation , orientation (vector space) , computer science , image (mathematics) , computer vision , satellite , artificial intelligence , control point , polynomial , algorithm , mathematics , geometry , mathematical analysis , biochemistry , chemistry , physics , astronomy , engineering , gene , aerospace engineering
The Rational Polynomial Coefficients (RPC) provided with the IKONOS images contains a large error and they need Ground Control Point (GCP) refinement. To present the technique of refinement of RPCs by the application of some appropriate transformation algorithm with some suitable number of GCPs in proper constellation in an optimal way to achieve high geometric accuracy during spatial data acquisition from IKONOS stereo image is the objective of this paper. From this study it was found that GCP refinement of RPCs by affine transformation with four GCPs in proper constellation is optimal for the orientation of the image pair under study, it was also found that at least two redundant GCPs are necessary for proper refinement by a particular transformation algorithm.