A new article is available in IPOL: http://www.ipol.im/pub/art/2016/124/
Miguel Colom, and Antoni Buades,
Analysis and Extension of the PCA Method, Estimating a Noise Curve from
a Single Image,
Image Processing On Line, 6 (2016), pp. 365–390.
https://doi.org/10.5201/ipol.2016.124
Abstract
In the article 'Image Noise Level Estimation by Principal Component
Analysis', S. Pyatykh, J. Hesser, and L. Zheng propose a new method to
estimate the variance of the noise in an image from the eigenvalues of
the covariance matrix of the overlapping blocks of the noisy image.
Instead of using all the patches of the noisy image, the authors propose
an iterative strategy to adaptively choose the optimal set containing
the patches with lowest variance. Although the method measures uniform
Gaussian noise, it can be easily adapted to deal with signal-dependent
noise, which is realistic with the Poisson noise model obtained by a
CMOS or CCD device in a digital camera.
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