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Proceedings Paper

Pyramidal predictive image coding with polynomial transforms
Author(s): Boris Escalante-Ramirez; Santiago Venegas-Martinez; Francisco Garcia-Ugalde
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Paper Abstract

We present a predictive image coding technique based on the polynomial transform. This is an image representation model that analyzes an image by locally expanding it into a weighted sum of orthogonal polynomials. The scheme proposed in this paper is a Laplacian-like pyramidal structure. Based on interpolation and deblurring algorithms implemented by means of the polynomial transform, our method improves the prediction of an image at a certain spatial scale from its representation at a lower scale, thereby reducing the entropy of the prediction error image, in comparison with the Laplacian pyramid and the scale-space image coding schemes.

Paper Details

Date Published: 3 March 1995
PDF: 11 pages
Proc. SPIE 2418, Still-Image Compression, (3 March 1995); doi: 10.1117/12.204121
Show Author Affiliations
Boris Escalante-Ramirez, National Univ. of Mexico (Mexico)
Santiago Venegas-Martinez, National Univ. of Mexico (Mexico)
Francisco Garcia-Ugalde, National Univ. of Mexico (Mexico)


Published in SPIE Proceedings Vol. 2418:
Still-Image Compression
Majid Rabbani; Edward J. Delp; Sarah A. Rajala, Editor(s)

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