Algebraic relational approach to conflating images

Boris Kovalerchuk; William Q. Sumner

doi:10.1117/12.492928

23 September 2003 Algebraic relational approach to conflating images

Proceedings Volume 5093, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery IX; (2003) https://doi.org/10.1117/12.492928
Event: AeroSense 2003, 2003, Orlando, Florida, United States

Abstract

An approach to conflation/registration of images that does not depend on identifying common points is being developed. It uses the method of algebraic invariants to provide a common set of coordinates to images using continuous chains of line segments formally described as polylines. It is shown the invariant algebraic properties of the polylines provide sufficient information to automate conflation. When there are discrepancies between the image data sets, robust measures of the possibility and quality of match (measures of correctness) are necessary. Decision making and the usability of the resulting conflation depends on such quality control measures. These measures may also be used to mitigate the effects of sensor and observational artifacts. This paper describes the theory of algebraic invariants and presents a conflation/registration method and measures of correctness of feature matching.

Citation Download Citation

Boris Kovalerchuk and William Q. Sumner "Algebraic relational approach to conflating images", Proc. SPIE 5093, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery IX, (23 September 2003); https://doi.org/10.1117/12.492928

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