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Proceedings Paper

Integer wavelet transformations with predictive coding improves 3D similar image set compression
Author(s): Xiaojun Qi; John M. Tyler; Oleg S. Pianykh
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Paper Abstract

Lossless compression techniques are essential in archival and communication of large amounts of homogeneous data in radiological image databases. This paper exploits dependencies that exist between the pixel intensities in three dimensions to improve compression for a set of similar medical images. These 3-D dependencies are systematically presented as histograms, plots of wavelet decomposition coefficients, feature vectors of wavelet decomposition coefficients, entropy and correlation. This 3-D dependency is called set redundancy for medical image sets. Predictive coding is adapted to set redundancy and combined with integer wavelet transformations to improve compression. This set compression improvement is demonstrated with 3-D sets of magnetic resonance (MR) brain images.

Paper Details

Date Published: 26 March 2001
PDF: 12 pages
Proc. SPIE 4391, Wavelet Applications VIII, (26 March 2001); doi: 10.1117/12.421205
Show Author Affiliations
Xiaojun Qi, Louisiana State Univ. (United States)
John M. Tyler, Louisiana State Univ. (United States)
Oleg S. Pianykh, Louisiana State Univ. (United States)

Published in SPIE Proceedings Vol. 4391:
Wavelet Applications VIII
Harold H. Szu; David L. Donoho; Adolf W. Lohmann; William J. Campbell; James R. Buss, Editor(s)

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