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Proceedings Paper

Maximizing image variance in rendering of volumetric data sets
Author(s): Bjoern Olstad
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Paper Abstract

An algorithm is presented for rendering of volumetric data sets. The aim of the algorithm is to maximize the image variance in a volumetric rendering where a three-dimensional data set is projected onto a view plane through the perspective mapping. The pixel values in the rendered image are associated with a variable-sized attribute vector extracted along a line in the volumetric data set. Several algorithms are presented for transforming this variable-sized attribute vector into a fixed-sized attribute vector. The fixed-sized attribute vectors provide a multi-spectral image representation which is processed with the Karhunen-Loeve transformation in order to separate the information content into orthogonal components and ordered according to the associated eigenvalues. The components in the Karhunen-Loeve transform can be displayed individually as intensity images or three components can be selected and mapped into a coloring scheme such as the HSV color model.

Paper Details

Date Published: 26 June 1992
PDF: 12 pages
Proc. SPIE 1660, Biomedical Image Processing and Three-Dimensional Microscopy, (26 June 1992); doi: 10.1117/12.59597
Show Author Affiliations
Bjoern Olstad, Norwegian Institute of Technology (Norway)


Published in SPIE Proceedings Vol. 1660:
Biomedical Image Processing and Three-Dimensional Microscopy
Raj S. Acharya; Carol J. Cogswell; Dmitry B. Goldgof, Editor(s)

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