Mixed Noise Removal by Weighted Encoding With Sparse Nonlocal Regularization

  title={Mixed Noise Removal by Weighted Encoding With Sparse Nonlocal Regularization},
  author={Jielin Jiang and Lei Zhang and Jian Yang},
  journal={IEEE Transactions on Image Processing},
Mixed noise removal from natural images is a challenging task since the noise distribution usually does not have a parametric model and has a heavy tail. One typical kind of mixed noise is additive white Gaussian noise (AWGN) coupled with impulse noise (IN). Many mixed noise removal methods are detection based methods. They first detect the locations of IN pixels and then remove the mixed noise. However, such methods tend to generate many artifacts when the mixed noise is strong. In this paper… CONTINUE READING
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