Improved Method for Blind Estimation of the Variance of Mixed Noise Using Weighted LMS Line Fitting Algorithm

Sergey K. Abramov , Victoriya Zabrodina , Vladimir V. Lukin , Benoit Vozel (1) , Kacem Chehdi (1) , Jaakko T. Astola

1 IETR - Institut d'Électronique et des Technologies du numéRique

The paper addresses blind evaluation of the parameters of mixed noise in images. The conventional approach is based on line fitting in the scatter-plot of local variance estimates using LMS algorithm. This does not utilize the fact that the points in the scatter pot typically appear in clusters that depend on the image. It is shown that the use of weighted LMS algorithm that takes into account the number of points in clusters provides considerable improvement in the accuracy of line fitting and, thus, better estimation of the parameters of mixed noise.

Sergey K. Abramov, Victoriya Zabrodina, Vladimir V. Lukin, Benoit Vozel, Kacem Chehdi, et al.. Improved Method for Blind Estimation of the Variance of Mixed Noise Using Weighted LMS Line Fitting Algorithm. International Symposium on Circuits and Systems Nano-Bio Circuit Fabrics and Systems (ISCAS 2010), May 2010, Paris, France. pp.2642-2645. ⟨hal-00947031⟩