An easily computable eight times overcomplete ICA method for image data

Authors:
Mika Inki
Affiliations:
Neural Networks Research Centre, Helsinki University of Technology, HUT, Finland
Venue:
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
Year:
2006

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Abstract

Here we present a procedure for finding an eight times overcomplete ICA description of image data using the symmetries defined by the rigid motions of a square. The procedure for estimating the basis requires only a small change to any classic ICA procedure and the data representation in this overcomplete description is unique. Coding and decoding in this description are essentially as easy as in classic ICA methods. We also show that this description is genuinely more sparse than a non-overcomplete ICA method.