Compressed sensing and Bayesian experimental design

  title={Compressed sensing and Bayesian experimental design},
  author={Matthias W. Seeger and Hannes Nickisch},
We relate compressed sensing (CS) with Bayesian experimental design and provide a novel efficient approximate method for the latter, based on expectation propagation. In a large comparative study about linearly measuring natural images, we show that the simple standard heuristic of measuring wavelet coefficients top-down systematically outperforms CS methods using random measurements; the sequential projection optimisation approach of (Ji & Carin, 2007) performs even worse. We also show that… CONTINUE READING
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