Abstract
Speckle noise removal plays a crucial role in ultrasound (US) image diagnosis, since the visual quality of the US images are largely corrupted by speckle noise. Numerous speckle noise removal techniques have been proposed in the literature based on anisotropic filtering, wavelets and morphology; however they have some major problems like loss of edge information, texture information and inability to remove low frequency noise. Despeckling of US images is usually carried out using conventional anisotropic diffusion or speckle reducing anisotropic diffusion. However, despeckling US images may not be able to preserve the edges which comprises of important clinical information. To overcome the issues in speckle noise removal (despeckling) of US images, contourlet transform based anisotropic nonlinear diffusion filtering is proposed in this paper. Contourlet transform improves some important features like multiscale and directionality. Adaptive nonlinear diffusion has been incorporated in anisotropic filtering to improve the filtering performance. The comparison performance of the proposed method with other despeckling techniques indicates that it has better noise removal performance for medical US images.
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Jubairahmed, L., Satheeskumaran, S. & Venkatesan, C. Contourlet transform based adaptive nonlinear diffusion filtering for speckle noise removal in ultrasound images. Cluster Comput 22 (Suppl 5), 11237–11246 (2019). https://doi.org/10.1007/s10586-017-1370-x
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DOI: https://doi.org/10.1007/s10586-017-1370-x