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Proceedings Paper

Genetic fusion of registered images
Author(s): Renaud de Peufeilhoux
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Paper Abstract

An edge detection algorithm allows the edge points to be extracted which will be joined in a further stage to form lines. When performed on a single image of a scene, this edge detection is difficult because it is not easy to distinguish in the image what is the essential information (linked to the shapes to recover) and what are contingent details; then meaningful edge points may be missed or, on the contrary, some superfluous contours may be selected. If multispectral images were available, the separation between essential and contingent information would be easier to get. The essential information may be considered as common to the different spectral images, as if to characterize a `species' we get not only a member of the species but a population. The proposed method for edge detection of multispectral images relies on the fusion of statistics computed within small corresponding neighborhoods of the images. The statistics are related to similarities between images and the particularity of the method comes from the fact that these statistics are only meaningful when all the corresponding neighborhoods are considered. The same parameters for one single spectral image are not so meaningful and don't lead to the right decision. This hidden information at monochromatic levels, which is revealed at multispectral levels, is called genetic information. That is why the proposed method is called `genetic fusion'. As an example, genetic fusion is applied to edge detection of SPOT multispectral images.

Paper Details

Date Published: 1 February 1992
PDF: 5 pages
Proc. SPIE 1607, Intelligent Robots and Computer Vision X: Algorithms and Techniques, (1 February 1992); doi: 10.1117/12.57074
Show Author Affiliations
Renaud de Peufeilhoux, Thomson-CSF (France)

Published in SPIE Proceedings Vol. 1607:
Intelligent Robots and Computer Vision X: Algorithms and Techniques
David P. Casasent, Editor(s)

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