Scan-based wavelet transform for huge 3D volume data

Authors:
Anis Meftah;Marc Antonini
Affiliations:
I3S Laboratory UMR 6070, University of Nice-Sophia Antipolis and CNRS, France;I3S Laboratory UMR 6070, University of Nice-Sophia Antipolis and CNRS, France
Venue:
PCS'09 Proceedings of the 27th conference on Picture Coding Symposium
Year:
2009

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Abstract

This paper introduces an efficient method to compute the wavelet transform for huge 3D volume data like seismic data or 3D medical images with minimum resources. This method consists in a local data processing while reducing considerably the memory requirements. The resulting wavelet transform is identical to the one obtained if the whole 3D object was stored in memory. Experimental results show that the proposed method permits to reduce the memory requirements to the minimum with a low computation time due to the low complexity algorithm.