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Erschienen in:
2014 | OriginalPaper | Buchkapitel
A Shearlet-Based Filter for Low-Dose Mammography
verfasst von : Huiqin Jiang, Yunyi Zhang, Ling Ma, Xiaopeng Yang, Yumin Liu
Erschienen in: Breast Imaging
Verlag: Springer International Publishing
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To improve image quality of low-dose mammography images, we study a new approach of removing Poisson noise from a degraded image in shearlet domain. We first transform Poisson noise into a near Gaussian noise by a shearlet-based multiply variance stabilizing transform (VST). Second, the initial positions of ideal shearlet coefficients are found by thresholding Gaussian noise coefficients. Third, an iterative scheme is proposed to estimate non-noise coefficients from the found initial ideal shearlet coefficients. Finally, the reduced noise image is obtained by the inverse shearlet transform on the estimated coefficients. The main contribution is to combine thresholding and the iterative scheme. A range of experiments demonstrate that the proposed method outperforms the traditional shearlet-based method.