Convex Denoising using Non-Convex Tight Frame Regularization

@article{Parekh2015ConvexDU,
  title={Convex Denoising using Non-Convex Tight Frame Regularization},
  author={Ankit Parekh and Ivan W. Selesnick},
  journal={IEEE Signal Processing Letters},
  year={2015},
  volume={22},
  pages={1786-1790}
}
This letter considers the problem of signal denoising using a sparse tight-frame analysis prior. The l1 norm has been extensively used as a regularizer to promote sparsity; however, it tends to under-estimate non-zero values of the underlying signal. To more accurately estimate non-zero values, we propose the use of a non-convex regularizer, chosen so as to ensure convexity of the objective function. The convexity of the objective function is ensured by constraining the parameter of the non… CONTINUE READING
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