文章基本信息

标题：Analysis and Extension of the PCA Method, Estimating a Noise Curve from a Single Image
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作者：Miguel Colom ; Antoni Buades
期刊名称：Image Processing On Line
电子版ISSN：2105-1232
出版年度：2016
卷号：6
页码：365-390
DOI：10.5201/ipol.2016.124
出版社：Image Processing On Line
摘要：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.