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Gaussian noise estimation methods in images

A common and investigated problem in image processing is noise, especially Gaussian, because it affects image quality and the subsequent treatment. Therefore, different filtering techniques are created and improved every day. Some of these techniques require to know the approximate value of the noise level, so it is essential to develop noise estimation methods. Given that there are not comparatives studies of these techniques, in this work an evaluation of six relevant methods was developed. The techniques were implemented as java plugins for the free access software ImageJ. They were evaluated and compared using standard and synthetic images. Several of the methods assume certain parameter values. Here, the validity of these assertions was studied, observing that they were not valid in most of them. It was found, in most cases the evaluated techniques did not allow to obtain a good estimation of the noise level.