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access icon free Multiscale adaptive regularisation Savitzky–Golay method for speckle noise reduction in ultrasound images

© The Institution of Engineering and Technology
Received 02/05/2017, Accepted 01/10/2017, Revised 05/09/2017, Published 03/10/2017

Speckle noise is one of the major artefacts in ultrasound images. The denoising faces the trade-off between noise suppression and structural preservation. In this study, multiscale adaptive regularisation Savitzky–Golay (MARSG) method, the new filter for removing speckle noise, is proposed. The proposed method combines the benefit of the multiscale analysis and the outstanding noise removing capability of Savitzky–Golay (SG) filter. The Laplacian pyramid is employed to separate an image into the noise, texture and object layers. Adaptive regularisation Savitzky–Golay (ARSG) filter is developed as the denoising filter in the noise and the texture layers. The denoising of the ARSG filter is adaptively adjusted in order to preserve the edges of objects in the image. The experiments on the synthetic and ultrasound images demonstrated that MARSG method offered better balance between noise removal and structural preservation than non-linear multiscale wavelet diffusion, feature-enhanced speckle reduction and regularised SG filter.

Inspec keywords: biomedical ultrasonics; image denoising; ultrasonic imaging; image filtering; image texture; medical image processing; speckle; adaptive filters; wavelet transforms

Other keywords: noise suppression; ultrasound imaging; structural preservation; image filtering; adaptive regularisation Savitzky-Golay filter; nonlinear multiscale wavelet diffusion; MARSG method; multiscale adaptive regularisation Savitzky-Golay method; speckle noise reduction; image denoising; Laplacian pyramid; regularised SG filter; image texture; feature enhanced speckle reduction; ARSG filter

Subjects: Computer vision and image processing techniques; Patient diagnostic methods and instrumentation; Biology and medical computing; Sonic and ultrasonic radiation (medical uses); Function theory, analysis; Integral transforms; Measurement by acoustic techniques; Optical, image and video signal processing; Integral transforms; Sonic and ultrasonic radiation (biomedical imaging/measurement); Sonic and ultrasonic applications

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