Stuart J. Golin

DVI image compression: second generation

The goal of this compression algorithm is to exploit the i750TM video processor to achieve VCR quality video at CD-ROM data rates. The algorithm uses motion compensation with fractional-pixel displacements to produce good predicted images. The residual errors are then encoded using pyramid and vector-quantization techniques. A binary tree is used to efficiently encode large areas of the image with the same displacement vector, and large areas where the residual errors quantize to zero. The remaining quantities are statistically encoded for the programmable statistical decoder of the i750 video processor. This second-generation algorithm has achieved its goal and is now incorporated in current DVI products.

A simple variable-length code

Abstract This paper describes a Simple Variable-Length Code (SVLC) that is very efficient, typically within 1% of Huffman coding. Furthermore, it has very low overhead when the ordering of the probabilities is approximately monotonie, which is important for short messages. An inexpensive hardware implementation is described, and a software implementation is included. This paper presents two fast and intuitive algorithms for producing SVLC codes, and an algorithm that produces optimal codes. The fast algorithms are shown to be efficient for several distributions, and optimal when the probabilities are exponentially distributed. The complexities of the fast algorithms are O( K ), and that of the optimal one is O( K log K ), where K is the size of the symbol alphabet.