Wavelet based 3D compression with fast random access for very large volume data

In this paper we propose a wavelet based method for compressing volumetric data with little loss in quality allowing fast random access to individual voxels within the volume. Such a method is important since storing and visualising very large volumes impose heavy demands on internal memory and external storage facilities, a problem not likely to become less in the future, making it accessible only to users with huge and expensive computers. Experimental results on the CT dataset of the Visible Human have shown that our method provides very high compression rates with fairly fast random access.