Iterative Source-Channel Decoding for Error-Resilient Image Transmission Using a Markov Random Field Source Model

Jörg Kliewer, Norbert Görtz, Alfred Mertins

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations

Abstract

In this paper, we propose a joint source-channel decoding approach for the robust image transmission over wireless channels. In addition to the explicit redundancy coming from channel codes, we also use implicit residual source redundancy for error protection. The source redundancy is modeled by a Markov random field (MRF) source model, which considers the residual spatial correlation after source encoding. Due to the link between MRFs and the Gibbs distribution, the source decoder can be implemented with low complexity. At the decoder we use an iterative source-channel decoder which can be obtained in the same manner as for serially concatenated channel codes. As a novel result we show that this iterative decoding scheme in combination with a simplified joint allocation of source and channel coding rates can be successfully employed for recovering the image data, especially when the channel is highly corrupted.

Original languageEnglish (US)
Pages (from-to)305-310
Number of pages6
JournalITG-Fachbericht
Issue number181
StatePublished - Jan 1 2004
Externally publishedYes
Event5th International ITG Conference on Source and Channel Coding (SCC) - Erlangen, Germany
Duration: Jan 14 2004Jan 16 2004

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture

Fingerprint Dive into the research topics of 'Iterative Source-Channel Decoding for Error-Resilient Image Transmission Using a Markov Random Field Source Model'. Together they form a unique fingerprint.

Cite this