The implications of Boltzmann-type machines for SAR data processing: a preliminary survey

Citation

Luttrell S P, June 1985, The implications of Boltzmann-type machines for SAR data processing: a preliminary survey, RSRE technical report (Malvern, UK), 3815

Abstract

We propose that Markov random field models (MRFs) be used as a framework within which to construct models of synthetic aperture radar (SAR) images. We clarify the relationship between this class of models and the Boltzmann machine (BM) of artificial intelligence. We then generalise the BM training procedure and use it to train MRF models. Using this technique we investigate the ability of a simple MRF texture model to learn a texture by maximising a relative entropy objective function. We find that the marriage of MRF models with the BM training procedure is fruitful.

Links

  • Remastered paper in PDF format (2 column)
  • Remastered paper in Mathematica
  • Reproduction of results using Mathematica