| |
Abstract:
An image is often represented by a set of detected features.
We get an enormous compression by representing images in this way.
Furthermore, we get a representation which is little affected by
small amounts of noise in the image. However, features are
typically chosen in an ad hoc manner. We show how a good set of
features can be obtained using sufficient statistics. The idea of
sparse data representation naturally arises. We treat the
1-dimensional and 2-dimensional signal reconstruction problem to
make our ideas concrete.
|
