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Proceedings Paper

Spatial analysis of image registration methodologies for fusion applications
Author(s): Peter J. Doucette; Henry J. Theiss; Edward M. Mikhail; Dennis J. Motsko
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Paper Abstract

Data registration is the foundational step for fusion applications such as change detection, data conflation, ATR, and automated feature extraction. The efficacy of data fusion products can be limited by inadequate selection of the transformation model, or characterization of uncertainty in the registration process. In this paper, three components of image-to-image registration are investigated: 1) image correspondence via feature matching, 2) selection of a transformation function, and 3) estimation of uncertainty. Experimental results are presented for photogrammetric versus non-photogrammetric transfer of point features for four different sensor types and imaging geometries. The results demonstrate that a photogrammetric transfer model is generally more accurate at point transfer. Moreover, photogrammetric methods provide a reliable estimation of accuracy through the process of error propagation. Reliable local uncertainty derived from the registration process is particularly desirable information to have for subsequent fusion processes. To that end, uncertainty maps are generated to demonstrate global trends across the test images. Recommendations for extending this methodology to non-image data types are provided.

Paper Details

Date Published: 16 May 2011
PDF: 12 pages
Proc. SPIE 8053, Geospatial InfoFusion Systems and Solutions for Defense and Security Applications, 80530G (16 May 2011); doi: 10.1117/12.886166
Show Author Affiliations
Peter J. Doucette, Contractor for NGA (United States)
Henry J. Theiss, Contractor for NGA (United States)
Edward M. Mikhail, Purdue Univ. (United States)
Dennis J. Motsko, National Geospatial-Intelligence Agency (United States)


Published in SPIE Proceedings Vol. 8053:
Geospatial InfoFusion Systems and Solutions for Defense and Security Applications
Matthew F. Pellechia; Richard Sorensen; Shiloh L. Dockstader; Rudy G. Benz; Bernard V. Brower, Editor(s)

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