Ultrasound imaging is one of the most important and cheapest instrument used for diagnostic purpose among the clinicians. Due to inherent limitations of acquisition methods and systems, ultrasound images are corrupted by the multiplicative speckle noise that degrades the quality and most importantly texture information present in the ultrasound image. In this paper, we proposed an algorithm based on a new multiscale geometric representation as discrete ripplet transform and non-linear bilateral filter in order to reduce the speckle noise in ultrasound images. Ripplet transform with their different features of anisotropy, localization, directionality and multiscale is employed to provide effective representation of the noisy coefficients of log transformed ultrasound images. Bilateral filter is applied to the approximation ripplet coefficients to improve the denoising efficiency and preserve the edge features effectively. The performance of the proposed method is evaluated by conductive extensive simulations using both synthetic speckled and real ultrasound images. Experiments show that the proposed method provides better results of removing the speckle and preserving the edges and image details as compared to several existing methods. 
Ripplet domain non-linear filtering for speckle reduction in ultrasound medical images