Ultrasonic speckle denoising using the combination of wavelet transform and Wiener filter

Ultrasonic images are inherently affected by multiplicative noise, which is due to the coherent wave interference in tissue. This paper presents a method for ultrasonic speckle denoising using the combination of wavelet transform and wiener filter to effectively reduce the speckle noise while preserving the resolvable details. In our method, the steps involved are finding the 2D discrete wavelet transform of the logarithmic image. Then, the wiener filter is used to apply over areas in each detail subband (HH,HL and LH). Next the inverse wavelet transform is computed and applying the inverse logarithm. To evaluate the denoising performance, mean square error (MSE), signal to mean square error (S/mse) and edge preservation (/spl beta/) are used. From the experimental results, we found that our approach leads to an effective method for ultrasonic speckle denoising.