Speckle Reduction in Medical Ultrasound Images using Bilateral filter in Wavelet domain

Abstract

The inherent noise speckle imposes several limitations on diagnosis and post processing of ultrasound images and hence feature preserved denoising is necessary for better diagnosis. This paper presents a speckle reduction method using bilateral filter in wavelet domain for ultrasound images. The image is first transformed to approximation and detail subbands using Discrete Wavelet Transform (DWT). Bilateral filtering is used to reduce the noise present in the approximation subband and NeighShrink is used for processing the coefficients of detail subbands. The application of the bilateral filter again at the last step in spatial domain improves the efficiency of the proposed scheme in terms of denoising and edge preservation. Image quality evaluation metrics such as Peak Signal to Noise Ratio (PSNR), Root Mean Square Error (RMSE), Edge Preservation Index (EPI), Coefficient of Correlation (CoC), Feature Similarity Index (FSIM) and Quality Index (QI) are used to evaluate the performance of the proposed method. The Visual comparison of despeckled images and higher values of image quality metrics demonstrate the ability of the proposed scheme for noise suppression and edge preservation.