 |
 |
 |
 |
Assignment of Multiplicative Mixtures in Natural Images.
Odelia Schwartz, Terrence J. Sejnowski, and Peter Dayan.
Advances
in Neural Information Processing Systems 17, 2004.
--------------------------------------------------------------------------------
In the analysis of natural images, Gaussian scale mixtures (GSM)
have been used to account for the statistics of filter responses, and
to
inspire hierarchical cortical representational learning schemes.
GSMs pose a critical assignment problem, working out which
filter responses were generated by a common multiplicative factor.
We present a new approach to solving this assignment problem
through a probabilistic extension to the basic GSM, and show how
to perform inference in the model using Gibbs sampling. We demonstrate
the efficacy of the approach on both synthetic and image data.
--------------------------------------------------------------------------------
Preprint
(168K, pdf)
/ Back