Geometric symmetry in the quadratic Fisher discriminant operating on image pixels

Computer Science – Information Theory

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Accepted for publication in IEEE Transactions on Information Theory

Scientific paper

10.1109/TIT.2006.871581

This article examines the design of Quadratic Fisher Discriminants (QFDs) that operate directly on image pixels, when image ensembles are taken to comprise all rotated and reflected versions of distinct sample images. A procedure based on group theory is devised to identify and discard QFD coefficients made redundant by symmetry, for arbitrary sampling lattices. This procedure introduces the concept of a degeneracy matrix. Tensor representations are established for the square lattice point group (8-fold symmetry) and hexagonal lattice point group (12-fold symmetry). The analysis is largely applicable to the symmetrisation of any quadratic filter, and generalises to higher order polynomial (Volterra) filters. Experiments on square lattice sampled synthetic aperture radar (SAR) imagery verify that symmetrisation of QFDs can improve their generalisation and discrimination ability.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Geometric symmetry in the quadratic Fisher discriminant operating on image pixels does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Geometric symmetry in the quadratic Fisher discriminant operating on image pixels, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Geometric symmetry in the quadratic Fisher discriminant operating on image pixels will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-550749

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.