The iDUDE Framework for Grayscale Image Denoising

@article{Motta2011TheIF,
  title={The iDUDE Framework for Grayscale Image Denoising},
  author={Giovanni Motta and Erik Ordentlich and Ignacio Ram{\'i}rez and Gadiel Seroussi and Marcelo J. Weinberger},
  journal={IEEE Transactions on Image Processing},
  year={2011},
  volume={20},
  pages={1-21}
}
We present an extension of the discrete universal denoiser DUDE, specialized for the denoising of grayscale images. The original DUDE is a low-complexity algorithm aimed at recovering discrete sequences corrupted by discrete memoryless noise of known statistical characteristics. It is universal, in the sense of asymptotically achieving, without access to any information on the statistics of the clean sequence, the same performance as the best denoiser that does have access to such information… CONTINUE READING
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