Automatic Window Size Estimation For Speckle Noise Filters

Speckle noise is a random granular texture that is inherent to ultrasonic imaging. It makes object recognition more difficult for both humans and computers. There are several speckle filters in the literature which aim to mitigate the speckle noise while trying to preserve the borders of the objects. However, the choice of the filter parameters makes them hard to work with and, sometimes, may be arbitrary. Especially in window-based filters, the users have to select the window size. An excessively large window may deform or even erase the object of interest. On the other hand, a small window may leave the speckle noise unchanged. We propose a method that automatically determines the window size based on the speckle noise pattern. This technique calculates the average distance between the local maxima and the nearest local minimum, and vice-versa. This method provides a reliable parameter to characterize the speckle noise. We applied this technique using median filter, whose only parameter is the window size. The proposed method was validated numerically with root mean squared error and structural similarity and it presented better results than the direct application of median filter. Through visual assessment, it is possible to see that the proposed method is able to remove the speckle texture and preserve the object edges, while the direct application of the filter generated blurred borders.