title: Improved image decoding over noisy channels using minimum mean-squared estimation and a Markov mesh.
abstract: Joint source-channel (JSC) decoding based on residual source redundancy is a technique for providing channel robustness to quantized data. Previous work assumed a model equivalent to viewing the encoder/noisy channel tandem as a discrete hidden Markov model (HMM) with transmitted indices the hidden states. We generalize this HMM-based (1-D) approach for images, using the more powerful hidden Markov mesh random field (HMMRF) model. While previous state estimation methods for HMMRFs base estimates on only a causal subset of the observed data, our new method uses both causal and anticausal subsets. For JSC-based image decoding, the new method provides significant benefits over several competing techniques.
authors.forename: M
authors.initials: M
authors.lastname: Park
authors.forename: D J
authors.initials: DJ
authors.lastname: Miller