Open AccessMultiscale adaptive regularisation Savitzky–Golay method for speckle noise reduction in ultrasound images
Author(s) -
Saing Vera,
Vorasayan Pongpat,
Suwanwela Nijasri C.,
Auethavekiat Supatana,
Chinrungrueng Chedsada
Publication year - 2018
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2017.0391
Subject(s) - speckle noise , noise reduction , computer science , computer vision , artificial intelligence , noise (video) , filter (signal processing) , wavelet , median filter , speckle pattern , adaptive filter , pattern recognition (psychology) , mathematics , algorithm , image processing , image (mathematics)
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.