Efficient 1-pass prediction for volume compression

Abstract

The aim is to compress and decompress structured volume graphics in a lossless way. Lossless compression is necessary when the original scans must be preserved. Algorithms must deliver a fair compression ratio, have low run-time and space complexity, and work numerically robust. We have developed PRO to meet the goals. PRO traces runs of voxels in 3D and compensates for noise in the least significant bits by way of using differential pulse-code modulation (DPCM). PRO reduces data to 46% of the original size at best, and 54% on average. A combination of PRO and Worst-Zip (Zip with weakest compression enabled) gives reductions of 34% at best, and 45% on average. The combination takes the same or less time than Best-Zip, and gives 13%, respectively 5%, better results. To conduct the tests, we have written a non-optimised, sequential prototype of PRO, processed CT and MRI scans of different size and content, and measured speed and compression ratio. © Springer-Verlag Berlin Heidelberg 2005.