1. A method for processing a sequence of night vision image datasets, wherein said sequence comprises at least two image datasets each having at least two pixels, wherein each pixel has an intensity value, said method comprising: calculating, based on estimated intensity derivatives in each pixel, a structure tensor for each pixel in an image dataset comprised in said sequence of image datasets, and performing an eigen-decomposition of said structure tensor, calculating values in a summation kernel based on said structure tensor for each pixel in said image dataset, calculating a weighted intensity value for each pixel in said image dataset, using as weights the values in said summation kernel, storing said weighted intensity value for each pixel in said image dataset as a processed intensity value for each corresponding pixel in a processed output image dataset, the method furthermore comprising: rotating a local coordinate system in which the summation kernel is described resulting in that the coordinate axes of said local coordinate system coincide with the directions of the eigenvectors of said structure tensor, where said eigenvectors are described in the global coordinate system of the image dataset, and scaling the coordinate axes of the local coordinate system in which the summation kernel is described by an amount related to the eigenvalues of the structure tensor via a width function w(λ i )=σ i , and wherein said eigenvalues depend on the amount of intensity variation in the direction of their corresponding eigenvectors, and in addition the width function being a decreasing function depending on the noise level in each pixel such that w(0)=σ max and lim a→∞ w(a)=σ min .