Chen Yuan, Raheja Amar
Department of Computer Science, California State Polytechnic University, Pomona, 3801 W. Temple Avenue, Pomona, CA 91768, USA.
Conf Proc IEEE Eng Med Biol Soc. 2005;2005:3129-32. doi: 10.1109/IEMBS.2005.1617138.
In this paper, a wavelet domain method for speckle noise filtering is presented. It uses non-decimated wavelet transform and Generalized Cross Validation thresholding technique. The spatial correlation of ultrasound speckle noise is broken by multiresolution analysis. Level dependent thresholding removes noise in the wavelet domain based on automatic estimation of noise energy in each subband. The efficacy of this filter is demonstrated on both simulated and real medical ultrasound images. The result is shown to be promising and outperforms other de-noising approaches. A single adjustable parameter can be used by medical experts to balance the relevant image feature preservation and the speckle noise suppression. Lifting scheme as a way of constructing new biorthogonal wavelets based on existing wavelet as well as a way of performing wavelet transform is studied in this research to improve the performance of wavelet de-noising.
