Adaptive speckle reduction in ultrasound images using fuzzy logic on Coefficient of Variation

Abstract

Abstract Speckle reduction is an important pre-processing stage for ultrasound medical image processing. In this paper, an adaptive fuzzy logic approach for speckle noise reduction in ultrasound images is presented. In the proposed method, adaptiveness is incorporated at two levels. In the first level, applying fuzzy logic on the coefficients of variation computed from the noisy image, image regions are classified. The best suitable filter for the particular image region is adaptively selected by the system yielding appreciable improvement in noise suppression and preservation of image structural details. At the second level, to distinguish between edges and noise, the proposed method uses a weighted averaging filter. The structural similarity measure, which depends on the nature of image and quantity of noise present in the image, is used as the tuning parameter. Thus with two levels of adaptiveness, the proposed method has better edge preservation compared to existing methods. Experimental results of the proposed method for natural images, Field II simulated images and real ultrasound images, show that proposed denoising algorithm has better noise suppression and is able to preserve edges and image structural details compared with existing methods.