An adaptive speckle suppression filter based on Nakagami distribution

Using a good statistical model of speckle formation is important in designing an adaptive filter for speckle reduction in ultrasound B-scan images. Most clinical ultrasound imaging systems use a nonlinear logarithmic function to reduce the dynamic range of the the input echo signal and emphasize objects with weak backscatter. Previously, the statistic of log-compressed images had been derived for Rayleigh and K distributions. In this paper, the statistics of log-compressed echo images is derived for a Nakagami distribution, more general than Rayleigh and with lower computational cost than K distribution, and used the extracted result for designing an unsharp masking filter to reduce speckle. To demonstrate the efficiency of the designed adaptive filter for removing speckle, we processed two original ultrasound images of kidney and liver.

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