Conference Paper

J. E. Fowler, K. C. Adkins, S. B. Bibyk, and S. C. Ahalt, "Differential Vector Quantization of Real-Time Video Using Entropy-biased ANN Codebooks," in Proceedings of the IEEE International Conference on Neural Networks, Orlando, FL, June 1994, vol. 3, pp. 1871-1876.

• Abstract:
  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 (ANN). 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.

• Text:

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