Adaptive Wavelet Transforms for Image Coding
Roger Claypoole (clayporl@rice.edu)
Electrical and Computer Engineering, Rice University
Geoffrey Davis (gdavis@cs.dartmouth.edu)
Department of Mathematics, Dartmouth College
Wim Sweldens (wim@research.bell-labs.com)
Bell Laboratories, Lucent Technologies
Richard Baraniuk (richb@rice.edu)
Electrical and Computer Engineering, Rice University
We introduce a new adaptive transform for wavelet-based image coding.
The lifting framework for wavelet construction motivates our analysis and
provides new insight into the problem.
Since the adaptive transform is non-linear,
we examine the central issues of invertibility, stability, and
artifacts in its construction.
We describe a new type of
non-linearity: a set of linear predictors are chosen adaptively using a non-linear
selection function. We also describe how earlier families of
non-linear filter banks can be extended through the use of
prediction functions operating on a causal neighborhood.
We present preliminary results for a synthetic test image.