LOSSLESS COMPRESSION OF COMPUTER-GENERATED ANIMATION FRAMES

This article presents a new lossless compression algorithm for compute r animation image sequences. The algorithm uses transformation informa tion available in the animation script and floating point depth and ob ject number information at each pixel to perform highly accurate motio n prediction with very low computation. The geometric data (i.e., the depth and object number) can either be computed during the original re ndering process and stored with the image or computed on the fly durin g compression and decompression. In the former case the stored geometr ic data are very efficiently compressed using motion prediction and a new technique called direction coding, typically to 1 to 2 bits per pi xel. The geometric data are also useful in z-buffer image compositing, and this new compression algorithm offers a very low storage overhead method for saving the information needed for this compositing. The ov erall compression ratio of the new algorithm, including the geometric data overhead, is compared to conventional spatial linear prediction c ompression and block-matching motion prediction and is shown to be con sistently better, by a factor of 2 or more, even with large frame-to-f rame motion. The algorithm improves on a previous motion prediction al gorithm by incorporating block predictor switching and color ratio pre diction. The combination of these techniques gives compression ratios 30% better than those reported previously.