This is SPIRAL-TAP: Sparse Poisson Intensity Reconstruction ALgorithms—Theory and Practice

@article{Harmany2012ThisIS,
  title={This is SPIRAL-TAP: Sparse Poisson Intensity Reconstruction ALgorithms—Theory and Practice},
  author={Zachary T. Harmany and Roummel F. Marcia and Rebecca Willett},
  journal={IEEE Transactions on Image Processing},
  year={2012},
  volume={21},
  pages={1084-1096}
}
Observations in many applications consist of counts of discrete events, such as photons hitting a detector, which cannot be effectively modeled using an additive bounded or Gaussian noise model, and instead require a Poisson noise model. As a result, accurate reconstruction of a spatially or temporally distributed phenomenon (f*) from Poisson data (y) cannot be effectively accomplished by minimizing a conventional penalized least-squares objective function. The problem addressed in this paper… CONTINUE READING
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