Denoising of Ultrasonic Image via Double Density Dual Tree Wavelet Combined with Bivariate Shrinkage with Local Variance Estimation

The improved algorithm was proposed for reducing the ultrasonic image speckle noise and ameliorating image quality,in which the double density dual tree discrete wavelet transform(DD-DT DWT) was combined with the bivariate shrinkage function(BSF) with local variance estimation. The original image was firstly decomposed by the DD-DT DWT,then the threshold was estimated according to the noise model and the marginal variance of the local noisy wavelet coefficients and their parent coefficients,and the wavelet coefficients were shrunk by the BSF related to dependence of parent and son wavelet coefficients,in which all of 16 orientations were nonlinear processed adaptively,finally the denoised image was reconstructed by all the update coefficients. The improved algorithm was tested by simulated and actual data,and was compared with other wavelet denoising algorithms. The results indicate that the performances of the denoised image via the proposed algorithm are coincidently improved,and that the effective denoising of image and the preserving of particular are simultaneously obtained.