Abstract
Blur in X-ray radiographs not only reduces the sharpness of image edges but also reduces the overall contrast. The effective blur in a radiograph is the combined effect of blur from multiple sources such as the detector panel, X-ray source spot, and system motion. In this paper, we use a systems approach to model the point spread function (PSF) of the effective radiographic blur as the convolution of multiple PSFs, where each PSF models one of the various sources of blur. In particular, we model the combined contribution of X-ray source and detector blurs while assuming negligible contribution from other forms of blur. Then, we present a numerical optimization algorithm for estimating the source and detector PSFs from multiple radiographs acquired at different X-ray source to object (SOD) and object to detector distances (ODD). Finally, we computationally reduce blur in radiographs using deblurring algorithms that use the estimated PSFs from the previous step. Our approach to estimate and reduce blur is called SABER, which is an acronym for systems approach to blur estimation and reduction.
Highlights
X -RAY imaging systems are widely used for 2D and 3D non-destructive characterization and visualization of a wide range of objects
We focus on using Wiener filter [25], [28] and regularized least squares deconvolution [26]–[28] for deblurring radiographs
We presented a method to estimate both X-ray source and detector blur from radiographs of a Tungsten plate rollbar
Summary
X -RAY imaging systems are widely used for 2D and 3D non-destructive characterization and visualization of a wide range of objects. Beer’s law [30] is used to express the magnitude of X-ray attenuation within an object in terms of its thickness and material properties. X-ray attenuation is dependent on a material property called linear attenuation coefficient (LAC) which is a function of the object’s chemical composition, density, and X-ray energy. At detector pixel (i, j ) shown, according to Beer’s law, the ratio of the X-ray measurement with the object, Is (i, j ), and the X-ray measurement without the object, Ib(i, j ), is given by, Is (i, j ) = Ib(i, j ) S(E) exp E − μ (E,r) dr L(i, j ) dE, (1). We will call the expression on the right side of the equality in equation (1) as the ideal transmission function T (i, j ), i.e.,
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