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A general method of source coding over expansion is proposed in this paper,which enables one to reduce the problem of compressing an analog(continuous-valued source) to a set of much simpler problems, compressingdiscrete sources. Specifically, the focus is on lossy compression ofexponential and Laplacian sources, which is subsequently expanded using afinite alphabet prior to being quantized. Due to decomposability property ofsuch sources, the resulting random variables post expansion are independent anddiscrete. Thus, each of the expanded levels corresponds to an independentdiscrete source coding problem, and the original problem is reduced to codingover these parallel sources with a total distortion constraint. Any feasiblesolution to the optimization problem is an achievable rate distortion pair ofthe original continuous-valued source compression problem. Although finding thesolution to this optimization problem at every distortion is hard, we show thatour expansion coding scheme presents a good solution in the low distrotionregime. Further, by adopting low-complexity codes designed for discrete sourcecoding, the total coding complexity can be tractable in practice.

Lossy Compression of Exponential and Laplacian Sources using Expansion Coding