Speckle filtering of medical ultrasonic images using wavelet and guided filter.

Speckle noise is an inherent yet ineffectual residual artifact in medical ultrasound images, which significantly degrades quality and restricts accuracy in automatic diagnostic techniques. Speckle reduction is therefore an important step prior to the analysis and processing of the ultrasound images. A new de-noising method based on an improved wavelet filter and guided filter is proposed in this paper. According to the characteristics of medical ultrasound images in the wavelet domain, an improved threshold function based on the universal wavelet threshold function is developed. The wavelet coefficients of speckle noise and noise-free signal are modeled as Rayleigh distribution and generalized Gaussian distribution respectively. The Bayesian maximum a posteriori estimation is applied to obtain a new wavelet shrinkage algorithm. The coefficients of the low frequency sub-band in the wavelet domain are filtered by guided filter. The filtered image is then obtained by using the inverse wavelet transformation. Experiments with the comparison of the other seven de-speckling filters are conducted. The results show that the proposed method not only has a strong de-speckling ability, but also keeps the image details, such as the edge of a lesion.