Despeckling medical ultrasound images using the contourlet transform

Abstract

The narrowband ultrasound image suffers from a speckle noise. A novel method of medical ultrasound image despeckling using the contourlet transform is presented. The log transformed ultrasound image is contourlet transformed to obtain contourlet coefficients. The number of levels of Laplacian pyramidal decomposition, the number of directional decompositions to perform on each pyramidal level are determined. The transformed image is denoised by applying thresholding technique on individual bandpass subbands using a Bayes' shrinkage rule. The performance is measured in terms of variance, Mean Square Error (MSE), Signal to Noise Ratio (SNR), Peak Signal to Noise Ratio (PSNR) and Correlation Coefficient (CC). Finally, a comparison of performance of wavelet-based despeckling and contourlet based despeckling is provided. It is shown that the contourlet transform method has better performance than wavelet transform method. Despeckling is performed on medical ultrasound images to improve visual quality for better image analysis and diagnosis. Copyright © 2009 by IICAI.