Encoding visual information using anisotropic transformations

Encoding visual information using anisotropic transformations

The evolution of information in images undergoing fine-to-coarse anisotropic transformations is analyzed by using an approach based on the theory of irreversible transformations. In particular, we show that, when an anisotropic diffusion model is used, local variation of entropy production over spac...

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Veröffentlicht in:IEEE transactions on pattern analysis and machine intelligence 2001-02, Vol.23 (2), p.207-211
Hauptverfasser: Boccignone, G., Ferrearo, M., Caelli, T.
Format: Artikel
Sprache:eng
Schlagworte:
Anisotropic magnetoresistance
Anisotropy
Convergence
Data mining
Diffusion processes
Encoding
Entropy
Equations
Evolution
Image analysis
Information analysis
Intelligence
Pattern analysis
Production
Transformations
Visual
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Zusammenfassung:The evolution of information in images undergoing fine-to-coarse anisotropic transformations is analyzed by using an approach based on the theory of irreversible transformations. In particular, we show that, when an anisotropic diffusion model is used, local variation of entropy production over space and scale provides the basis for a general method to extract relevant image features.
ISSN:0162-8828
1939-3539
DOI:10.1109/34.908970