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.
Highlights
Kuan et al, 1987) use a defined filter window to estimate the local noise variance and perform the Ultrasonography (US) is one of the widely used individual unique filtering process
This study aims at introducing an algorithm by hybridizing bilateral filter with NeighShrink
This study aims at introducing a novel method which uses bilateral filter and the wavelet thresholding scheme NeighShrink to enhance the visual quality of ultrasound images for better diagnosis
Summary
Kuan et al, 1987) use a defined filter window to estimate the local noise variance and perform the Ultrasonography (US) is one of the widely used individual unique filtering process. One of the major drawbacks of the ultrasound spatial domain techniques, wavelet thresholding image is poor image quality due to speckle noise (Loizou techniques have been proposed for denoising of and Pattichis, 2008). In addition the presence of speckle complicates medical images (Fourati et al, 2005), in which the main the image processing tasks like segmentation critical task is the selection of threshold. Speckle suppression is essential to 1995) and BayesShrink (Chang et al, 2000) are the improve the visual quality and possibly the diagnostic different methods proposed for the selection of threshold potential of ultrasound imaging. Chen et al (2004) proposed a wavelet thresholding techniques have been developed for removing speckle scheme based on wavelet coefficients within a noise and retaining edge details in ultrasound images. Many noise reduction value. Chen et al (2004) proposed a wavelet thresholding techniques have been developed for removing speckle scheme based on wavelet coefficients within a noise and retaining edge details in ultrasound images. neighborhood and its improved version
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
