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Proceedings Paper

Space/error tradeoffs for lossy wavelet reconstruction
Author(s): Jonathan Frain; R. Daniel Bergeron
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Paper Abstract

Discrete Wavelet Transforms have proven to be a very effective tool for compressing large data sets. Previous research has sought to select a subset of wavelet coefficients based on a given space constraint. These approaches require non-negligible overhead to maintain location information associated with the retained coefficients. Our approach identifies entire wavelet coefficient subbands that can be eliminated based on minimizing the total error introduced into the reconstruction. We can get further space reduction (with more error) by encoding some or all of the saved coefficients as a byte index into a floating point lookup table. We demonstrate how our approach can yield the same global sum error using less space than traditional MR implementations.

Paper Details

Date Published: 25 January 2012
PDF: 13 pages
Proc. SPIE 8294, Visualization and Data Analysis 2012, 82940J (25 January 2012); doi: 10.1117/12.907544
Show Author Affiliations
Jonathan Frain, The Univ. of New Hampshire (United States)
R. Daniel Bergeron, The Univ. of New Hampshire (United States)


Published in SPIE Proceedings Vol. 8294:
Visualization and Data Analysis 2012
Pak Chung Wong; David L. Kao; Ming C. Hao; Chaomei Chen; Robert Kosara; Mark A. Livingston; Jinah Park; Ian Roberts, Editor(s)

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