Statistical independence is one of the most desirable properties for
a coordinate system for representing and modeling images.
In reality, however, truly independent coordinates may not exist for a given
set of images, or it may be computationally too difficult to obtain such
coordinates.
Therefore, it makes sense to obtain the least statistically dependent
coordinate system efficiently.
This basis---we call it Least Statistically-Dependent Basis (LSDB)---can
be rapidly computed by minimizing the sum of the differential entropy
of each coordinate in the basis library.
This criterion is quite different from the Joint Best Basis (JBB) proposed
by Wickerhauser.
We demonstrate the use of the LSDB for image modeling and compare its
performance with JBB and Karhunen-Loeve Basis (KLB).
Get the full paper: PDF file.
Get the official version via doi:10.1117/12.328146.
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