Bayesian Denoising: From MAP to MMSE Using Consistent Cycle Spinning

@article{Kazerouni2013BayesianDF,
  title={Bayesian Denoising: From MAP to MMSE Using Consistent Cycle Spinning},
  author={Abbas Kazerouni and Ulugbek Kamilov and Emrah Bostan and Michael Unser},
  journal={IEEE Signal Processing Letters},
  year={2013},
  volume={20},
  pages={249-252}
}
We introduce a new approach for the implementation of minimum mean-square error (MMSE) denoising for signals with decoupled derivatives. Our method casts the problem as a penalized least-squares regression in the redundant wavelet domain. It exploits the link between the discrete gradient and Haar-wavelet shrinkage with cycle spinning. The redundancy of the representation implies that some wavelet-domain estimates are inconsistent with the underlying signal model. However, by imposing… CONTINUE READING