Ultrasound Despeckling Using an Adaptive Window Stochastic Approach
A novel stochastically driven filtering method to despeckle B mode ultrasound images is presented. This method is motivated by viewing the pixel values as a stochastic process and removing outliers, where outliers are defined by local extrema. These outliers are removed by local averaging. This produces another image with new outliers (local extrema) and the process is iterated. With each iteration homogeneous regions become smoother while edges that defined these regions are preserved. By allowing a dynamically varying window to determine the local mean, we achieve equivalent results with fewer iterations.