In medical image processing, image denoising has become an essential requirement for correct diagnosis. This paper proposes a hybrid filter which employs Wavelet Packet Transforms and Wiener Filters for removal of noise in ultrasound images. Wavelet Packet Transforms is a generalization of the wavelet transforms that offers a rich set of decomposition structure. On the other hand, the Wiener filter tries to build an optimal estimate of the original image by enforcing a minimum mean-square error constraint between estimate and original image. In the first step, the multiplicative noise is modelled into an additive one followed by application of Discrete Wavelet Packet transforms. This is followed by application of Wiener Filter to the output obtained in the previous stage. The proposed algorithm is tested on different images and is found to produce better results in terms of the qualitative and quantitative measures of the image for both low and high values of noise variance in comparison to many existing techniques.

Speckle noise, Wavelet Packet Transforms, Noise variance, Wiener Filter, PSNR, Ultrasound

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