  In this paper, we study the use of GF(q)-quantized LDGM codes for binary
source coding. By employing quantization, it is possible to obtain binary
codewords with a non-uniform distribution. The obtained statistics is hence
suitable for optimal, direct quantization of non-uniform Bernoulli sources. We
employ a message-passing algorithm combined with a decimation procedure in
order to perform compression. The experimental results based on GF(q)-LDGM
codes with regular degree distributions yield performances quite close to the
theoretical rate-distortion bounds.
