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Using Projection Kurtosis Concentration Of Natural Images For Blind Noise Covariance Matrix Estimation
AbstractKurtosis 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.
Related Material
[pdf][bibtex]@InProceedings{Zhang_2014_CVPR,
author = {Zhang, Xing and Lyu, Siwei},
title = {Using Projection Kurtosis Concentration Of Natural Images For Blind Noise Covariance Matrix Estimation},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2014}
}
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