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Orthogonal pyramid transforms for image coding
 

Summary: Orthogonal pyramid transforms for
image coding
Edward H. Adelson and Eero Simoncelli
MIT Media Laboratory, Cambridge, MA 02139
Rajesh Hingorani
SRI David Sarnoff Research Center, Princeton NJ 08540
Abstract:
We describe a set of pyramid transforms that decompose an
image into a set of basis functions that are (a) spatial-frequency
tuned, (b) orientation tuned, (c) spatially localized, and (d)
self-similar. For computational reasons the set is also (e)
orthogonal and lends itself to (f) rapid computation. The systems
are derived from concepts in matrix algebra, but are
closely connected to decompositions based on quadrature
mirror filters. Our computations take place hierarchically,
leading to a pyramid representation in which all of the basis
functions have the same basic shape, and appear at many
scales. By placing the high-pass and low-pass kernels on
staggered grids, we can derive odd-tap QMF kernels that are
quite compact. We have developed pyramids using separable,

  

Source: Adelson, Edward - Computer Science and Artificial Intelligence Laboratory, Department of Brain and Cognitive Science, Massachusetts Institute of Technology (MIT)
Simoncelli, Eero - Center for Neural Science, New York University

 

Collections: Biology and Medicine; Computer Technologies and Information Sciences