A distributed source coding technique for highly correlated images using turbo-codes

According to the Slepian-Wolf theorem [1], the output of two correlated sources can be compressed to the same extent without loss, no matter if they communicate with each other or not, provided that the decompression takes place at a common decoder having both compressed outputs available. In this paper, as an application of the Slepian-Wolf theorem, an advanced distributed source coding scheme for correlated images is presented. Assuming that the correlated image is a noisy version of the original, the scheme involves modulo encoding of the pixel values and encoding (compression) of the resulting symbols with binary and nonbinary turbo-codes, so that rate savings are achieved practically without loss.