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Proceedings Paper

Image conflation and change detection using area ratios
Author(s): Boris Kovalerchuk; Michael Kovalerchuk; William Sumner; Adam Haase
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Paper Abstract

The problem of imagery registration/conflation and change detection requires sophisticated and robust methods to produce better image fusion, target recognition, and tracking. Ideally these methods should be invariant to arbitrary image affine transformations. A new abstract algebraic structural invariant approach with area ratios can be used to identify corresponding features in two images and use them for registration/conflation. Area ratios of specific features do not change when an image is rescaled or skewed by an arbitrary affine transformation. Variations in area ratios can also be used to identify features that have moved and to provide measures of image registration/conflation quality. Under more general transformations, area ratios are not preserved exactly, but in practice can often still be effectively used. The theory of area ratios is described and three examples of registration/conflation and change detection are described.

Paper Details

Date Published: 1 June 2005
PDF: 12 pages
Proc. SPIE 5806, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI, (1 June 2005); doi: 10.1117/12.603172
Show Author Affiliations
Boris Kovalerchuk, Central Washington Univ. (United States)
Michael Kovalerchuk, Central Washington Univ. (United States)
William Sumner, Central Washington Univ. (United States)
Adam Haase, Central Washington Univ. (United States)


Published in SPIE Proceedings Vol. 5806:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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