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26 June 1992 Maximizing image variance in rendering of volumetric data sets
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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.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Bjoern Olstad "Maximizing image variance in rendering of volumetric data sets", Proc. SPIE 1660, Biomedical Image Processing and Three-Dimensional Microscopy, (26 June 1992);

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