Optimal One-bit Quantization
Source:
IEEE Data Compression Conference (DCC) (2005)
Abstract:
We consider the problem of finding the optimal one-bit quantizer for
symmetric source distributions, with the Euclidean norm as the measure
of distortion. For fixed rate quantizers, we prove that for
(symmetric) monotonically decreasing source distributions with
ellipsoidal level curves, the centroids of the optimal 1-bit quantizer
must lie on the major axis of the ellipsoids. Under the same
assumptions on the source distribution, the centroids of the optimal
one-bit {\em variable-rate} quantizer lie on one of the axes of the
ellipsoid. If further, the source distribution $f(x)$ is log-concave
in $x$, the optimal 1-bit fixed-rate quantizer is unique and symmetric
about the origin. (The Gaussian is an example of a distribution that
satisfies all these conditions.) Under a further set of conditions on
the source distributions, we show that there is a threshold below
which the optimal fixed rate and variable rate quantizer are the
same.