Using Projection Kurtosis Concentration of Natural Images for Blind Noise Covariance Matrix Estimation

CVPR 2014

doi:10.1109/CVPR.2014.367 /cvpr/2014/zhang2014cvpr-using/

Abstract

Kurtosis of 1D projections provides important statistical characteristics of natural images. In this work, we first provide a theoretical underpinning to a recently observed phenomenon known as projection kurtosis concentration that the kurtosis of natural images over different band-pass channels tend to concentrate around a typical value. Based on this analysis, we further describe a new method to estimate the covariance matrix of correlated Gaussian noise from a noise corrupted image using random band-pass filters. We demonstrate the effectiveness of our blind noise covariance matrix estimation method on natural images.

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Cite

Text

Zhang and Lyu. "Using Projection Kurtosis Concentration of Natural Images for Blind Noise Covariance Matrix Estimation." Conference on Computer Vision and Pattern Recognition, 2014. doi:10.1109/CVPR.2014.367

Markdown

[Zhang and Lyu. "Using Projection Kurtosis Concentration of Natural Images for Blind Noise Covariance Matrix Estimation." Conference on Computer Vision and Pattern Recognition, 2014.](https://mlanthology.org/cvpr/2014/zhang2014cvpr-using/) doi:10.1109/CVPR.2014.367

BibTeX

@inproceedings{zhang2014cvpr-using,
  title     = {{Using Projection Kurtosis Concentration of Natural Images for Blind Noise Covariance Matrix Estimation}},
  author    = {Zhang, Xing and Lyu, Siwei},
  booktitle = {Conference on Computer Vision and Pattern Recognition},
  year      = {2014},
  doi       = {10.1109/CVPR.2014.367},
  url       = {https://mlanthology.org/cvpr/2014/zhang2014cvpr-using/}
}