Restoration of retinal images using anisotropic diffusion like algorithms

In image processing by the partial differential equations (PDEs), the first and the simplest models to have and to use are based on linear diffusion. The common difficulty of linear filters is the excessive smoothing which makes track edges difficult. Therefore, we can affirm that any improvement of these linear models must be carried out inside the operator of diffusion, thus sacrificing their linearity. We will see how these difficulties can be overcome by the use of the nonlinear models. The work achieved in this context will make the subject of the following paper. This document treats the automatic preprocessing of retinal vascular network in fundus images in order to improve the interpretation of the images for the doctors diagnosis. We propose to deal with the image restoration using original equation of anisotropic diffusion. Compared to traditional anisotropic diffusion filters, it has interesting capacities of smoothing, like the expected conservation of the details and contours, and especially a more continuous smoothing intra-area, avoiding the pitfall of stairs or of the mosaics.