Detection of Markov Random Fields on Two-Dimensional Intersymbol Interference Channels
<|reference_start|>Detection of Markov Random Fields on Two-Dimensional Intersymbol Interference Channels: We present a novel iterative algorithm for detection of binary Markov random fields (MRFs) corrupted by two-dimensional (2D) intersymbol interference (ISI) and additive white Gaussian noise (AWGN). We assume a first-order binary MRF as a simple model for correlated images. We assume a 2D digital storage channel, where the MRF is interleaved before being written and then read by a 2D transducer; such channels occur in recently proposed optical disk storage systems. The detection algorithm is a concatenation of two soft-input/soft-output (SISO) detectors: an iterative row-column soft-decision feedback (IRCSDF) ISI detector, and a MRF detector. The MRF detector is a SISO version of the stochastic relaxation algorithm by Geman and Geman in IEEE Trans. Pattern Anal. and Mach. Intell., Nov. 1984. On the 2 x 2 averaging-mask ISI channel, at a bit error rate (BER) of 10^{-5}, the concatenated algorithm achieves SNR savings of between 0.5 and 2.0 dB over the IRCSDF detector alone; the savings increase as the MRFs become more correlated, or as the SNR decreases. The algorithm is also fairly robust to mismatches between the assumed and actual MRF parameters.<|reference_end|>
@article{zhu2006detection,
    title={Detection of Markov Random Fields on Two-Dimensional Intersymbol
  Interference Channels},
    author={Ying Zhu, Taikun Cheng, Krishnamoorthy Sivakumar, and Benjamin J.
  Belzer},
    journal={arXiv preprint arXiv:cs/0609155},
    year={2006},
    archivePrefix={arXiv},
    eprint={cs/0609155},
    primaryClass={cs.IT math.IT}
}