Wavelet Based 3D Compression for Very Large Volume Data Supporting Fast Random Access

We propose a wavelet based method for compressing volumetric data with little loss in quality. The method supports fast random access to individual voxels within the compressed volume. Such a method is important since storing and visualising very large volumes impose heavy demands on internal memory and external storage facilities making it accessible only to users with huge and expensive computers. This problem is not likely to become less in the future. 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.