An Optimal Quantizer for Distributed Souce Coding

We present a extended algorithm to design an optimal scalar quantizer for distributed source coding in order to achieve a coding rate close to joint conditional entropy of the quantized frames given the side information. A simple model is considered in this paper. A tabu search method was combined with the Lloyd algorithm to select initial quantizers, which aims at minimizing the Lagrangian cost function and avoiding many poor local optima. Experimental results show the proposed method can improve rate-distortion performance for Gaussian scalar asymmetric case.