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Proceedings Paper

Quality metric for automated image registration performance prediction
Author(s): Kathy Minear; Jay K. Hackett
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Paper Abstract

Automated image geo-registration of military and defense related imagery can sometimes produce an unsuccessful result due to poor image quality, cloud cover, supporting data errors, and sensor phenomenology. In addition, there are many possible image processing algorithms that further compound the problem of prediction. An accurate mathematical model that is able to incorporate all these parameters and can predict the outcome of a registration event is not feasible. What is proposed here is a probabilistic approach to the problem. A robust quality metric that is able to determine the success of an autonomous registration will be discussed.

Paper Details

Date Published: 27 July 2000
PDF: 9 pages
Proc. SPIE 4054, Automated Geo-Spatial Image and Data Exploitation, (27 July 2000); doi: 10.1117/12.394107
Show Author Affiliations
Kathy Minear, Harris Corp. (United States)
Jay K. Hackett, Harris Corp. (United States)


Published in SPIE Proceedings Vol. 4054:
Automated Geo-Spatial Image and Data Exploitation
William E. Roper; Mark K. Hamilton, Editor(s)

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