Vector quantization by companding a union of Z-lattices

An encoding scheme is presented based on random coding theory in conjunction with companding techniques. This combination provides an easy design, and a low-storage quantizer. The groundwork of the study is Gaussian sources. The motivation is the attractive properties of Gaussian and Gaussian mixtures (GMs), and their applications in data compression. Here, codebooks are generated by companding a union of randomly translated cubic lattices. The compander functions operate scalar wise, providing an affordable encoding complexity that is rate independent. For such a codebook, an optimal search, and the indexing of the codevectors are addressed. Performance close to finite-dimensional random coding is achieved, while the complexity is not far from scalar coding. The structure of the codebook balances between complexity and performance. In comparison to some other methods, the advantage of the proposed scheme is more distinct for correlated sources.