  In this paper we propose a measure of anisotropy as a quality parameter to
estimate the amount of noise in noisy images. The anisotropy of an image can be
determined through a directional measure, using an appropriate statistical
distribution of the information contained in the image. This new measure is
achieved through a stack filtering paradigm. First, we define a local
directional entropy, based on the distribution of 0's and 1's in the
neigborhood of every pixel location of each stack level. Then the entropy
variation of this directional entropy is used to define an anisotropic measure.
The empirical results have shown that this measure can be regarded as an
excellent image noise indicator, which is particularly relevant for quality
assessment of denoising algorithms. The method has been evaluated with
artificial and real-world degraded images.
