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We consider the problem of compressing memoryless binary data with or withoutside information at the decoder. We review the parity- and the syndrome-basedapproaches and discuss their theoretical limits, assuming that there exists avirtual binary symmetric channel between the source and the side information,and that the source is not necessarily uniformly distributed. We take afactor-graph-based approach in order to devise how to take full advantage ofthe ready-available iterative decoding procedures when turbo codes areemployed, in both a parity- or a syndrome-based fashion. We end up obtaining aunified decoder formulation that holds both for error-free and for error-proneencoder-to-decoder transmission over generic channels. To support thetheoretical results, the different compression systems analyzed in the paperare also experimentally tested. They are compared against several differentapproaches proposed in literature and shown to be competitive in a variety ofcases.

A Unified Perspective on Parity- and Syndrome-Based Binary Data Compression Using Off-the-Shelf Turbo Codecs