DocumentCode
798582
Title
An extended class of scale-invariant and recursive scale space filters
Author
Pauwels, Eric J. ; Van Gool, Luc J. ; Fiddelaers, Peter ; Moons, Theo
Author_Institution
ESAT-M12, Katholieke Univ., Leuven, Belgium
Volume
17
Issue
7
fYear
1995
fDate
7/1/1995 12:00:00 AM
Firstpage
691
Lastpage
701
Abstract
Explores how the functional form of scale space filters is determined by a number of a priori conditions. In particular, if one assumes scale space filters to be linear, isotropic convolution filters, then two conditions (viz. recursivity and scale-invariance) suffice to narrow down the collection of possible filters to a family that essentially depends on one parameter which determines the qualitative shape of the filter. Gaussian filters correspond to one particular value of this shape-parameter. For other values the filters exhibit a more complicated pattern of excitatory and inhibitory regions. This might well be relevant to the study of the neurophysiology of biological visual systems, for recent research shows the existence of extensive disinhibitory regions outside the periphery of the classical center-surround receptive field of LGN and retinal ganglion cells (in cats). Such regions cannot be accounted for by models based on the second order derivative of the Gaussian. Finally, the authors investigate how this work ties in with another axiomatic approach of scale space operators which focuses on the semigroup properties of the operator family. The authors show that only a discrete subset of filters gives rise to an evolution which can be characterized by means of a partial differential equation
Keywords
Gaussian processes; group theory; image processing; neurophysiology; physiological models; spatial filters; visual perception; Gaussian filters; LGN; biological visual systems,; disinhibitory regions; excitatory regions; inhibitory regions; linear isotropic convolution filters; neurophysiology; partial differential equation; recursive scale space filters; retinal ganglion cells; scale-invariant filters; semigroup properties; shape-parameter; Biological system modeling; Cats; Cells (biology); Convolution; Neurophysiology; Nonlinear filters; Retina; Shape; Space exploration; Visual system;
fLanguage
English
Journal_Title
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher
ieee
ISSN
0162-8828
Type
jour
DOI
10.1109/34.391411
Filename
391411
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