Higher-order image statistics for unsupervised, information-theoretic, adaptive, image filtering

@article{Awate2005HigherorderIS,
  title={Higher-order image statistics for unsupervised, information-theoretic, adaptive, image filtering},
  author={Suyash P. Awate and Ross T. Whitaker},
  journal={2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05)},
  year={2005},
  volume={2},
  pages={44-51 vol. 2}
}
The restoration of images is an important and widely studied problem in computer vision and image processing. Various image filtering strategies have been effective, but invariably make strong assumptions about the properties of the signal and/or degradation. Therefore, these methods typically lack the generality to be easily applied to new applications or diverse image collections. This paper describes a novel unsupervised, information-theoretic, adaptive filter (UINTA) that improves the… CONTINUE READING
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