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Proceedings Paper

Orthogonal Pyramid Transforms For Image Coding.
Author(s): Edward H. Adelson; Eero Simoncelli; Rajesh Hingorani
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Paper 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 derived odd-tap QMF kernels that are quite compact. We have developed pyramids using separable, quincunx, and hexagonal kernels. Image data compression with the pyramids gives excellent results, both in terms of MSE and visual appearance. A non-orthogonal variant allows good performance with 3-tap basis kernels and the appropriate inverse sampling kernels.

Paper Details

Date Published: 13 October 1987
PDF: 9 pages
Proc. SPIE 0845, Visual Communications and Image Processing II, (13 October 1987); doi: 10.1117/12.976485
Show Author Affiliations
Edward H. Adelson, MIT Media Laboratory (United States)
Eero Simoncelli, MIT Media Laboratory (United States)
Rajesh Hingorani, SRI David Sarnoff Research Center (United States)

Published in SPIE Proceedings Vol. 0845:
Visual Communications and Image Processing II
T. Russell Hsing, Editor(s)

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