Differential vector quantization of real-time video using entropy-biased ANN codebooks

Describes hardware that has been built to compress video in real time using full-search vector quantization (VQ). This architecture implements a differential-vector-quantization (DVQ) algorithm which features entropy-biased codebooks designed using an artificial neural network (ANN). A special-purpose digital associative memory, the VAMPIRE chip, performs the VQ processing. The authors describe the DVQ algorithm, its adaptations for sampled NTSC composite-color video, and details of its hardware implementation. The authors conclude by presenting results drawn from real-time operation of the DVQ hardware