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Nonlinear Diffusion based on Bayesian Estimator in Laplacian Pyramid Domain for Ultrasonic Speckle Reduction

Md. Motiur Rahman, Mina, Mohammad Azim Published in Applied Sciences

International Journal of Applied Information Systems
Year of Publication: 2012
© 2012 by IJAIS Journal
10.5120/ijais12-450795
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  1. Md. Motiur Rahman, Mina and Mohammad Azim. Article: Nonlinear Diffusion based on Bayesian Estimator in Laplacian Pyramid Domain for Ultrasonic Speckle Reduction. International Journal of Applied Information Systems 4(9):27-30, December 2012. BibTeX

    @article{key:article,
    	author = "Md. Motiur Rahman and Mina and Mohammad Azim",
    	title = "Article: Nonlinear Diffusion based on Bayesian Estimator in Laplacian Pyramid Domain for Ultrasonic Speckle Reduction",
    	journal = "International Journal of Applied Information Systems",
    	year = 2012,
    	volume = 4,
    	number = 9,
    	pages = "27-30",
    	month = "December",
    	note = "Published by Foundation of Computer Science, New York, USA"
    }
    

Abstract

Laplacian pyramid based nonlinear diffusion (LPND) method is proposed for speckle noise reduction in medical ultrasound imaging. In this method, speckle is removed by nonlinear diffusion filtering of bandpass ultrasound images in Laplacian pyramid domain. For nonlinear diffusion in each pyramid layer, a Bayesian threshold is automatically determined by a variation of robust median estimator. The proposed LPND method reduces speckle noise significantly while preserving sharp image details. The superiority of the proposed LPND over the conventional LPND based on Gaussian filtering and LPND method based on Butterworth filtering based speckle reduction technique is demonstrated by applying them on synthetic and real ultrasound B-mode images.

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Keywords

Laplacian pyramid, multiscale analysis, nonlinear diffusion, speckle reduction, Bayesian estimator, ultrasound imaging