Short-block variable-rate trellis quantization

We present two methods for variable-rate trellis quantization. Both methods utilize trellis codes based on linear congruential (LC) recursions. LC code trellises have good pseudo-random properties and are easily adapted to serve reconstruction alphabets of different sizes. The first method finds an entropy-constrained code only by optimizing over a scale factor. The scale factor modifies an initial reproducer alphabet in order to skew the associated set of codeword lengths. Using a Lagrangian formulation and the maximum a posteriori (MAP) heuristic, we also develop an entropy-constrained trellis quantizer suitable for short blocks of data. Here the tailbiting BCJR algorithm is used to find the MAP path in the trellis. Simulation results for the Gaussian and Laplacian distributions show that the proposed method is competitive with the best in the literature.