I\'ve found a few ways of reducing noise from image, but my task is to measure it.
So I am interested in algorithm that will give me some number, noise rating. That
From a view of image processing, you can consult the classic paper "Image quality assessment: From error visibility to structural similarity" published in IEEE Transaction on Image Processing, which has already been cited 3000+ times according to Google Scholar. The basic idea is human's visual perception system is highly sensitive to structural similarity. However, noise (or distortion) often breaks such similarity. Therefore the authors tried to propose an objective measurement for image quality based on this motivation. You can find an implementation in MATLAB here.
To solve my problem I used next approach:
My noise rating is just number of pixels that were recognized as noise. To differentiate normal pixels from noise, I just calculated the medium value of its neighbor pixels and if its value was bigger than some critical value, we say that this one is noise.
if (ABS(1 - (currentPixel.R+currentPixel.G+currentPixel.B)/(neigborsMediumValues.R + neigboursMediumValues.G + neigboursMediumValues.B))) > criticalValue)
then
{
currentPixelIsNoise = TRUE;
}