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Wavelet Compression of Three-Dimensional Time-Lapse Biological Image Data

Published online by Cambridge University Press:  28 January 2005

H. Narfi Stefansson
Affiliation:
Department of Mathematics and Computer Science, University of Wisconsin, Madison, WI 53706, USA
Kevin W. Eliceiri
Affiliation:
Laboratory for Optical and Computational Instrumentation, University of Wisconsin, Madison, WI 53706, USA
Charles F. Thomas
Affiliation:
Laboratory for Optical and Computational Instrumentation, University of Wisconsin, Madison, WI 53706, USA
Amos Ron
Affiliation:
Department of Mathematics and Computer Science, University of Wisconsin, Madison, WI 53706, USA
Ron DeVore
Affiliation:
Department of Mathematics, University of South Carolina, Columbia, SC 29208, USA
Robert Sharpley
Affiliation:
Department of Mathematics, University of South Carolina, Columbia, SC 29208, USA
John G. White
Affiliation:
Laboratory for Optical and Computational Instrumentation, University of Wisconsin, Madison, WI 53706, USA
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Abstract

The use of multifocal-plane, time-lapse recordings of living specimens has allowed investigators to visualize dynamic events both within ensembles of cells and individual cells. Recordings of such four-dimensional (4D) data from digital optical sectioning microscopy produce very large data sets. We describe a wavelet-based data compression algorithm that capitalizes on the inherent redunancies within multidimensional data to achieve higher compression levels than can be obtained from single images. The algorithm will permit remote users to roam through large 4D data sets using communication channels of modest bandwidth at high speed. This will allow animation to be used as a powerful aid to visualizing dynamic changes in three-dimensional structures.

Type
BIOLOGICAL APPLICATIONS
Copyright
© 2005 Microscopy Society of America

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References

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