Integer wavelet transformations with predictive coding improves 3D similar image set compression

Xiaojun Qi; John M. Tyler; Oleg S. Pianykh

doi:10.1117/12.421205

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26 March 2001 Integer wavelet transformations with predictive coding improves 3D similar image set compression

Xiaojun Qi, John M. Tyler, Oleg S. Pianykh

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Proceedings Volume 4391, Wavelet Applications VIII; (2001) https://doi.org/10.1117/12.421205
Event: Aerospace/Defense Sensing, Simulation, and Controls, 2001, Orlando, FL, United States

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.

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Xiaojun Qi, John M. Tyler, and Oleg S. Pianykh "Integer wavelet transformations with predictive coding improves 3D similar image set compression", Proc. SPIE 4391, Wavelet Applications VIII, (26 March 2001); https://doi.org/10.1117/12.421205

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