Abstract
Methods are presented for reducing the table storage required when encoding and decoding with tree-structured vector quantization (TSVQ). The latter is a technique that requires many fewer arithmetic operations than unstructured vector quantization but at least as much storage. The new methods for reducing storage integrate a secondary quantizer into the design of TSVQ, so as to produce a tree structure that can be efficiently stored. Two of the techniques make use of the hierarchical nature of TSVQ. It is shown that, at the expense of a decrease in signal-to-quantization-noise ratio of 0.3 dB or less, encoder storage can be reduced by a factor of about ten and decoder storage can be reduced by a factor of about five. Comparisons are made with the method of codebook sharing.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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