Frame permutation quantization (FPQ) is a new vector quantization technique
using finite frames. In FPQ, a vector is encoded using a permutation source
code to quantize its frame expansion. This means that the encoding is a partial
ordering of the frame expansion coefficients. Compared to ordinary permutation
source coding, FPQ produces a greater number of possible quantization rates and
a higher maximum rate. Various representations for the partitions induced by
FPQ are presented and reconstruction algorithms based on linear programming and
quadratic programming are derived.
Permutation codes are a class of structured vector quantizers with a
computationally-simple encoding procedure. Here we provide an extension that
preserves the computational simplicity but yields improved operational
rate--distortion performance. The new class of vector quantizers has a codebook
comprising several permutation codes as subcodes. Methods for designing good
code parameters are given. One method depends on optimizing the rate allocation
in a shape--gain vector quantizer with gain-dependent wrapped spherical shape
codebook.