Spatially adaptive image denoising under overcomplete expansion

@article{Li2000SpatiallyAI,
  title={Spatially adaptive image denoising under overcomplete expansion},
  author={Xin Li and Michael T. Orchard},
  journal={Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101)},
  year={2000},
  volume={3},
  pages={300-303 vol.3}
}
  • Xin Li, Michael T. Orchard
  • Published in
    Proceedings International…
    2000
  • Computer Science
  • This paper presents a novel wavelet-based image denoising algorithm under overcomplete expansion. In order to optimize the denoising performance, we make a systematic study of both signal and noise characteristics under overcomplete expansion. High-band coefficients are viewed as the mixture of non-edge class and edge class observing different probability models. Based on improved statistical modeling of wavelet coefficients, we derive optimal MMSE estimation strategies to suppress noise for… CONTINUE READING

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