Real-time video compression using entropy-biased ANN codebooks
Stanley C. Ahalt, James E. Fowler · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1994
We describe 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. A special-purpose digital associative memory, the VAMPIRE chip, performs the VQ processing. We describe the DVQ algorithm, its adaptations for sampled NTSC composite- color video, and details of its hardware implementation. We conclude by presenting results drawn from real-time operation of the DVQ hardware.