In this study, the authors present an efficient technique for compression and coding of memoryless Laplacian sources, which uses variable-length code (VLC). That technique is based on the combination of two companding quantisers in the first case and three companding quantisers in the second case. These quantisers have disjoint support regions, different number of representation levels and different compressor functions. The closed-form expressions are obtained for the distortion, average bit rate and signal to quantisation noise ratio (SQNR). The presented numerical results point out the effects of rate-distortion (R-D) optimisation on the system performances. Since our model assumes the general case of Laplacian distribution, it has wide applications like the coding of speech and images. It is shown that the difference of SQNR of our model and classical companding quantiser based model is 2.8 dB for two quantisers and 4.2 dB in three quantisers model. The authors have also made a comparison between our model, combination of the optimal uniform quantiser and Huffmann lossless coder and combination of optimal companding quantiser and simple lossless coder.

In this paper a new model for compression of Laplacian source is given. This model consists of hybrid quantizer whose output levels are coded with Golomb-Rice code. Hybrid quantizer is combination of uniform and nonuniform quantizer, and it can be considered as generalized quantizer, whose special cases are uniform and nonuniformquantizers. We propose new generalized optimal compression function for companding quantizers. Hybrid quantizer has better performances (smaller bit-rate and complexity for the same quality) than both uniform and nonuniformquantizers, because it joins their good characteristics. Also, hybrid quantizer allows great flexibility, because there are many combinations of number of levels in uniform part and in nonuniformpart, which give similar quality. Each of these combinations has different bit-rate and complexity, so we have freedom to choose combination which is the most appropriate for our application, in regard to quality, bit-rate and complexity. We do not have such freedom of choice when we use uniform or nonuniform quantizers. Until now, it has been thought that uniform quantizer is the most appropriate to use with lossless code, but in this paper we show that combination of hybrid quantizer and lossless code gives better performances. As lossless code we use Golomb-Rice code because it is especially suitable for Laplacian source since it gives average bit-rate very close to the entropy and it is easier for implementation than Huffman code. Golomb-Rice code is used in many modern compression standards. Our model can be used for compression of all signals with Laplacian distribution.