Image filter by spatial correlation

A novel denoising filter that uses a spatial correlation measure between colors.

We propose a novel algorithm for removing noise in gray-levels and color images. The core concept on which is based the image filtering algorithm is a measure of spatial correlation between colors: we say that two colors are spatially correlated if these appear nearby in the image most often, with respect to the other pairs of colors. In the discrete case, this measure of spatial correlation is represented by an Adjacency matrix, which can be calculated efficiently. This is a non-iterative autocalibrable filter. Given its similarity in its implementation with the bilateral filter (FB), comparisons were made with this kind of filters using a current technique which estimates the parameters on the FB. It can be seen that the proposed filter generally produces better results than the FB.

Usage instructions inside the function file.

The algorithm was presented in spanish in the 12th edition of the International Congress on Computer Science (CORE 2012), (30 November 2012).