Wavelet based Despeckling of Medical Ultrasound Images with Bilateral filter

Speckle is a random multiplicative noise which obscures the perception and extraction of fine details in ultrasound image and despeckling is necessary for better diagnosis. In this paper an algorithm for despeckling of medical ultrasound images is proposed, which is based on wavelet thresholding and bilateral filtering in transform domain. NeighShrink is used for thresholding the wavelet coefficients of the detail subbands of an image decomposed using a wavelet filter bank. Bilateral filtering is applied to the approximation subband and also after reconstruction of the image. The combination of bilateral filtering and NeighShrink effectively preserve edges and eliminates noise. The algorithm is tested against the ultrasound image of gallbladder and synthetically speckled image. The simulation results show that the proposed algorithm gives better performance in terms of Peak Signal to Noise Ratio (PSNR) and Edge Preservation Factor (EPF).