Scan-based wavelet transform for huge 3D volume data
Anis Meftah, Marc Antonini · 2009
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.