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Proceedings Paper

Gram-Gabor approach to optimal image representation
Author(s): Moshe Porat; Yehoshua Y. Zeevi
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Paper Abstract

The Gram determinant technique is applied to signal representation by non-orthogonal bases. A special case of image representation in biological and machine vision using Gabor elementary functions (GEFs) is considered. It is shown that, in general, the Gram determinant is a better approach to computation of the expansion coefficients than the one using bi-orthonormal auxiliary functions. An optimal representation by finite sets of coefficients is attained without a significant computational effort and the resultant reconstruction error converges monotonically with the addition of basis’ components to the reconstruction set. The Gram approach appears to be in a better accord with biological findings, regarding information processing along the visual pathway, compared to the conventional bi-orthogonal scheme.

Paper Details

Date Published: 1 September 1990
PDF: 5 pages
Proc. SPIE 1360, Visual Communications and Image Processing '90: Fifth in a Series, (1 September 1990); doi: 10.1117/12.24161
Show Author Affiliations
Moshe Porat, Technion--Israel Institute of Technology (Israel)
Yehoshua Y. Zeevi, Technion--Israel Institute of Technology (Israel)


Published in SPIE Proceedings Vol. 1360:
Visual Communications and Image Processing '90: Fifth in a Series
Murat Kunt, Editor(s)

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