Adaptive fractal filtering of echocardiograms

Abstract

Echocardiograms are inherently corrupted by the speckle noise. Elimination of the noise is usually treated with low-pass filters which can degrade edges in the image. Adaptive approaches employ masks for edges and restrict low-pass filtering mainly to homogeneous regions. Masks are based on statistical parameters or gradients. In this paper are applied local dimension matrices from fractal model as masks. Experimental tests are conducted for two simple low-pass filters (i) average filter and Gaussian filter (ii) and using three multifractal measures known from the literature - MIN, MAX and OSC measure. Obtained results for adaptive approaches show improvements over non-adaptive approaches in all analyzed scenarios.