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Proceedings Paper

Semi-autonomous registration of satellite imagery using feature fitting
Author(s): Jody L. Smith; Sheila E. Motomatsu; John G. Taylor; Karen J. Jefferson; Brian R. Stallard
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Paper Abstract

Interband coregistration of multispectral satellite imagery is essential to exploiting the spectral information inherent in these data. A semi-automatic image registration method has been developed for Multispectral Thermal Imager (MTI) data. This registration method, based on feature fitting within the image, is applicable to the 14 MTI spectral bands that contain ground information; these spectral bands range from 0.45 to 10.7micrometers . The feature fitting registration method requires selection of an appropriate scene feature in the image, usually a crossroad or other feature with moderately high contrast to compute the required shift in x and y for each band. This paper describes the algorithm and provides examples of images registered using this method. Preliminary results show that for MTI image registration, feature fitting yields better results than cross-correlation. Results also show that this algorithm works well for a broad variety of scenes; this algorithm has been applied to images with scene content ranging from desert images with very little structure to heavily forested images. This method has been developed in support of the MTI mission, but may easily be extended for use on image data collected by other multispectral sensors.

Paper Details

Date Published: 20 August 2001
PDF: 8 pages
Proc. SPIE 4381, Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VII, (20 August 2001); doi: 10.1117/12.437034
Show Author Affiliations
Jody L. Smith, Sandia National Labs. (United States)
Sheila E. Motomatsu, Sandia National Labs. (United States)
John G. Taylor, Sandia National Labs. (United States)
Karen J. Jefferson, Sandia National Labs. (United States)
Brian R. Stallard, Sandia National Labs. (United States)

Published in SPIE Proceedings Vol. 4381:
Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VII
Sylvia S. Shen; Michael R. Descour, Editor(s)

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