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Proceedings Paper

Using image local response for efficient image fusion with the hybrid evolutionary algorithm
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Paper Abstract

Image fusion serves as the basis for automatic target recognition; it maps images of teh same scene received from different sensors into a common reference system. A novel fusion method is described that employs image local response and the hybrid evolutionary algorithm (HEA). Given geometric transformation A(V) under parameter vector V (e.g. affine image transformation) of the images subjected to fusion, image local response is defined as image transform components of the parameter vector V are applied to the image, and the corresponding variations of the least squared differences of the gray levels of the two images (i.e. before and after parameter variation) form the image response matrix. The transform R(V) extracts only the dynamic contents of the image, i.e. the salient features that are most sensitive to geometric transformation A(V). Since R(V) maps the image onto itself, the result of the mapping is largely invariant to the type of the sensor that was used to obtain the image. Once the response matrices are built for all images subjected to fusion, HEA is used to map the images into the common reference system.

Paper Details

Date Published: 21 September 2004
PDF: 8 pages
Proc. SPIE 5426, Automatic Target Recognition XIV, (21 September 2004); doi: 10.1117/12.541887
Show Author Affiliations
Igor V. Maslov, CUNY/Graduate Ctr. (United States)
Izidor Gertner, CUNY/City College (United States)

Published in SPIE Proceedings Vol. 5426:
Automatic Target Recognition XIV
Firooz A. Sadjadi, Editor(s)

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