Loss of information in images undergoing fine-to-coarse image transformations is analyzed by using an approach based on the theory of irreversible transformations. It is shown that entropy variation along scales can be used to characterize basic, low-level information and to gauge essential perceptual components of the image. The method is extended to the case of anisotropic diffusion and an algorithm based on entropy variation is presented that extracts relevant features of the image, showing in particular how to discriminate between smooth, textured and edge-type regions.
Visual information from anisotropic transformations / G. Boccignone, M. Ferraro, T. Caelli - In: Image Analysis and Processing, 1999. Proceedings. International Conference on[s.l] : IEEE, 1999. - ISBN 0769500404. - pp. 334-339 (( Intervento presentato al 10. convegno International Conference on Image Analysis and Processing tenutosi a Venezia nel 1999 [10.1109/ICIAP.1999.797617].
Visual information from anisotropic transformations
G. BoccignonePrimo
;
1999
Abstract
Loss of information in images undergoing fine-to-coarse image transformations is analyzed by using an approach based on the theory of irreversible transformations. It is shown that entropy variation along scales can be used to characterize basic, low-level information and to gauge essential perceptual components of the image. The method is extended to the case of anisotropic diffusion and an algorithm based on entropy variation is presented that extracts relevant features of the image, showing in particular how to discriminate between smooth, textured and edge-type regions.File | Dimensione | Formato | |
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