  We introduce a universal quantization scheme based on random coding, and we
analyze its performance. This scheme consists of a source-independent random
codebook (typically_mismatched_ to the source distribution), followed by
optimal entropy-coding that is_matched_ to the quantized codeword distribution.
A single-letter formula is derived for the rate achieved by this scheme at a
given distortion, in the limit of large codebook dimension. The rate reduction
due to entropy-coding is quantified, and it is shown that it can be arbitrarily
large. In the special case of "almost uniform" codebooks (e.g., an i.i.d.
Gaussian codebook with large variance) and difference distortion measures, a
novel connection is drawn between the compression achieved by the present
scheme and the performance of "universal" entropy-coded dithered lattice
quantizers. This connection generalizes the "half-a-bit" bound on the
redundancy of dithered lattice quantizers. Moreover, it demonstrates a strong
notion of universality where a single "almost uniform" codebook is near-optimal
for_any_ source and_any_ difference distortion measure.
