Abstract
In this paper matching of SAR and optical remote sensing images in object space is investigated. First, the matching performance of descriptors and localizers for point features extracted from preprocessed images is analyzed. In particular, the increase in matching performance when making use of approximate localization information is documented. Secondly, the combined geocoding of SAR and optical image data using both orbit information and digital surface models as well as matched points is introduced and investigated using a radar-photogrammetric least-squares adjustment approach.
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Hellwich, O., Wefelscheid, C., Lukaszewicz, J., Hänsch, R., Siddique, M.A., Stanski, A. (2013). Integrated Matching and Geocoding of SAR and Optical Satellite Images. In: Sanches, J.M., Micó, L., Cardoso, J.S. (eds) Pattern Recognition and Image Analysis. IbPRIA 2013. Lecture Notes in Computer Science, vol 7887. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38628-2_95
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DOI: https://doi.org/10.1007/978-3-642-38628-2_95
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