Experimental evaluation of filters used for removing speckle noise and enhancing ultrasound image quality

Abstract

In the modern-days diagnostics, ultrasound is considered a significant non-invasive imaging technique. However, ultrasound images are frequently contaminated by multiplicative speckle noise. Speckle noise is produced by constructive and destructive interference between ultrasound waves when the object being measured is smaller than the wavelength of the beam. The removal of speckle noise in ultrasound images is possible by using various filters. The current experimental study is aimed at finding the most suitable de-speckling filters for enhancing ultrasound images. The present study involves 102-abdomen ultrasound images degraded by speckle noise and the analysis of eight de-speckling filters (i.e., Mean, Median, Kuan, Lee, Frost, Adaptive Homomorphic, Wiener and Anisotropic Diffusion) is developed to find the optimum de-speckling filter. The results of the given filters are analyzed using the five quality metrics (i.e., PSNR, RMSE, SSI, STM, and SSIM). The metrics are further investigated by using the statistical tests (i.e., one-way ANOVA and Tukey’s post hoc test) to support the experimental evaluation. Simulation results showed that the Frost and adaptive Homomorphic filters work well for the ultrasound images degraded with higher value of speckle noise. From the proposed research, it is easy to select the optimal filter, which helps doctors to get fine details of the image.