New anisotropic diffusion operator in images filtering

Abstract

Abstract The anisotropic diffusion filters have become in the fundamental bases to address the medical images noise problem. The main attributes of these filters are: the noise removal effectiveness and the preservation of the information belonging to the edges that delimit the objects of an image. Due to these excellent attributes, through this article, a comparative study is proposed between a new diffusion operator and the Lorentz operator, proposed by the pioneers of anisotropic diffusion. For this, a strategy consisting of two phases is designed. In the first, called operator construction, the composition of functions is used to generate a new diffusion operator that meets with the conditions reported for this kind of the mathematical object. In the second phase, denominated filtering, a synthetic cardiac images database, based on computed tomography, is filtered using the aforementioned operators. According with the value obtained for the peak of the signal-to-noise ratio, the new operator shows similar performance to the Lorentz operator. The implementation of this new operator contributes to the generation of new knowledge in digital image processing context.