A MODIFIED ADAPTIVE WAVELET SHRINKAGE SPECKLE FILTER FOR ULTRASOUND IMAGES

Abstract

The usage of ultrasound imaging for medical diagnosis is limited due to the presence of speckle noise. In this study Modified Adaptive Wavelet Shrinkage Filter (MAWSF) in the translational invariant domain is proposed for the removal of speckle noise. The adaptive wavelet threshold function removes the fixed bias of soft thresholding. A new inter-scale dependency model is proposed, to perform a primary clustering of signal of interest and noise. Then, anew sub-band adaptive threshold is determined for all high frequency sub-bands at various decomposition levels, to shrink the noisy coefficients. Experiment is conducted on several ultrasound scan images. The results show that this method yields better visual quality and Peak Signal to Noise Ratio (PSNR). Improvement in preservation of edge details is also found measured with Edge Preservation Index (EPI) measure.