Morphological diversity and source separation

@article{Bobin2006MorphologicalDA,
  title={Morphological diversity and source separation},
  author={J{\'e}r{\^o}me Bobin and Yassir Moudden and Jean-Luc Starck and Michael Elad},
  journal={IEEE Signal Processing Letters},
  year={2006},
  volume={13},
  pages={409-412}
}
This letter describes a new method for blind source separation, adapted to the case of sources having different morphologies. We show that such morphological diversity leads to a new and very efficient separation method, even in the presence of noise. The algorithm, coined multichannel morphological component analysis (MMCA), is an extension of the morphological component analysis (MCA) method. The latter takes advantage of the sparse representation of structured data in large overcomplete… CONTINUE READING
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