Systolic Architectures for Finite-State Vector Quantization

Abstract

We present a new systolic architecture for implementing Finite State Vector Quantization in real-time for both speech and image data. This architecture is modular and has a very simple control flow. Only one processor is needed for speech compression. A linear array of processors is used for image compression; the number of processors needed is independent of the size of the image. We also present a simple architecture for converting line- scanned image data into the format required by this systolic architecture. Image data is processed at a rate of 1 pixel per clock cycle. An implementation at 31.5 MHz can quantize 1024 x 1024 pixel images at 30 frames/sec in real-time. We describe a VLSI implementation of these FSTSVQ processors.