Anzeige
Erschienen in:
2014 | OriginalPaper | Buchkapitel
Non-subsampled Contourlet Transform-Based Image Denoising in Ultrasound Images Using Elliptical Directional Windows and Block-Based Noise Estimation
verfasst von : J. Jai Jaganath Babu, Gnanou Florence Sudha
Erschienen in: Intelligent Computing, Networking, and Informatics
Verlag: Springer India
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Abstract
Speckle noise reduction is an important preprocessing stage for ultrasound medical image processing. In this paper, a despeckling algorithm is proposed based on non-subsampled contourlet transform (NSCT). This transform has the property of high directionality, anisotropy, and translation invariance which can be controlled by non-subsampled filter banks. This paper aims to estimate the noise-free coefficients in the directional subband by applying minimum mean square estimate (MMSE). Signal variance is estimated from the elliptical directional window, and noise variance is estimated from block-based approach and is compared with the MAD approach. Experimental results of proposed method are compared with existing methods in terms of signal-to-noise ratio (SNR) and edge preservation index.