Entropy coding is a type of lossless coding to compress digital data by representing frequently occurring patterns with few bits and rarely occurring patterns with many bits. Two most popular entropy coding schemes are Huffman coding and arithmetic coding [1]. The basic idea in Huffman coding is to assign short codewords to those input blocks with high probabilities and long codewords to those with low probabilities. Extended Huffman coding is the procedure of determining the optimal length of codewords for blocks of two or more symbols. In this paper we concerned with blocks of two, three, four and five symbols [1].

In this paper we propose a model of the two-level scalar quantizer with extended Huffman coding and variable decision threshold. We decide that the new quantizer model has only two representation levels due to small model complexity and the possibility of the efficient use of the Huffman coding procedure. Variable decision threshold is proposed so the representation levels’ assymetry can be achieved. The basic idea described in this paper is that, unlike to the Lloyd-Max's quantizer, the asymmetry of the representation levels is assumed such that to provide an unequal probability of representation levels for the symmetric Gaussian probability density function (PDF)[2],[3],[4]. Representation levels are determined from the centroid condition. Variable decision threshold is determined depending on signal quality that wants to be achieved. The proposed quantizer model is optimal when the variable decision threshold is equal to zero [1],[2]. The goal of designing the proposed model is the approaching of the average bit rate to the source entropy as close as possible.