SPECKLE REDUCTION IN ULTRASOUND IMAGES USING NEIGHSHRINK AND BILATERAL FILTERING

Abstract

Speckle is a random multiplicative noise which obscures the perception and extraction of fine details in ultrasound images and speckle reduction is necessary to improve the visual quality of ultrasound images for better diagnosis. This study aims at introducing an algorithm by hybridizing bilateral filter with NeighShrink. The bilateral filter is applied before decomposition and after reconstruction of the image using discrete wavelet transform to improve the denoising efficiency and preserve the edge features effectively. The wavelet thresholding scheme NeighShrink is used for thresholding of wavelet coefficients. The algorithm is tested with synthetically speckled and real ultrasound images. Quality evaluation metrics such as Peak Signal to Noise Ratio (PSNR), Edge Preservation Index (EPI) and Correlation Coefficient (CoC) are used to assess the performance of the proposed method. Experimental results show that the proposed scheme improves the visual quality of ultrasound images by suppressing the speckle noise while retaining edges.