Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/1594
Title: Advanced Stochastic Models for Partially Developed Speckle
Authors: Daba, Jihad S. 
Jreije, Philip
Affiliations: Department of Electrical Engineering 
Keywords: Doubly stochastic filtered process
Poisson point process
Segmentation
Ultrasound
Subjects: Speckle
Issue Date: 2009
Part of: International journal of electronics and communication engineering
Volume: 3
Issue: 3
Start page: 183
End page: 187
Abstract: 
Speckled images arise when coherent microwave, optical, and acoustic imaging techniques are used to image an object, surface or scene. Examples of coherent imaging systems include synthetic aperture radar, laser imaging systems, imaging sonar systems, and medical ultrasound systems. Speckle noise is a form of object or target induced noise that results when the surface of the object is Rayleigh rough compared to the wavelength of the illuminating radiation. Detection and estimation in images corrupted by speckle noise is complicated by the nature of the noise and is not as straightforward as detection and estimation in additive noise. In this work, we derive stochastic models for speckle noise, with an emphasis on speckle as it arises in medical ultrasound images. The motivation for this work is the problem of segmentation and tissue classification using ultrasound imaging. Modeling of speckle in this context involves partially developed speckle model where an underlying Poisson point process modulates a Gram-Charlier series of Laguerre weighted exponential functions, resulting in a doubly stochastic filtered Poisson point process. The statistical distribution of partially developed speckle is derived in a closed canonical form. It is observed that as the mean number of scatterers in a resolution cell is increased, the probability density function approaches an exponential distribution. This is consistent with fully developed speckle noise as demonstrated by the Central Limit theorem.
URI: https://scholarhub.balamand.edu.lb/handle/uob/1594
Open URL: Link to full text
Type: Journal Article
Appears in Collections:Department of Electrical Engineering

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