University of Valencia
Empirical statistical analysis of phases in Gabor filtered natural images
Thursday 07th of February 2013 at 12:00pm
The talk will show the results of an empirical statistical analysis of
images processed by complex Gabor-like filters. The analysis intends to
be a compilation of statistical facts, which could be use to better
model the human visual system by including phase information.
It is widely accepted that a model of the human visual system should
contain a first linear stage where the image is processed by Gabor-like
filters, and a second step where coefficients are non-linearly combined.
A lot of effort has been put in modeling this non-linear combination.
Most models employ the absolute value of the coefficients and ignore the
sign (or phase) [1-5]. The first contributions in modeling the phase
were mainly based on phase congruence [6,7]. In  a great contribution
was done mainly proposing a multidimensional phase distribution model
which we employ in our analysis. Our analysis is motivated from the
experience we acquired in the complex ICA context . We started to
model simultaneously modulus and phase and we realized that more
analysis of the empirical behaviour should be done.
Analyzing marginal, conditional and multidimensional empirical
distributions we found interesting behaviours. For instance non trivial
dependencies between moduli and phases are observed, thus the
coefficients show eliptically asymmetric distribution. Also, there is
more intrascale than interscale dependency, thus extending the phase
congruence point of view.
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