Abstract | ||
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In this paper, we present a point spread function (PSF) mod- elling technique to improve restoration of x-ray diffraction pattern (XRD). Different diffraction areas have different dis- tortion orientations due to diffuse light distortion (DLD). A new multiple PSF model is introduced and used to restore XRD data. Raw PSFs are collected from isolated spots from x-ray diffraction pattern in high resolution areas which rep- resent orientation of DLDs. An adaptive ridge regression (ARR) technique is used to remove noise from the raw PSF. A target Gaussian function is used to model the raw PSFs. A gradient descent algorithm (GDA) is used to find optimum parameters in a Gaussian function. A set of XRD data are restored by an iterative deconvolution algorithm (IDA) using the modelled PSFs. Experimental results using a single and multiple PSFs are presented and discussed. We show that by using a multiple PSF model in the deconvolution algorithm improved restored X-ray patterns are obtained and as a result the symmetry estimator and χ 2 are improved. |
Year | Venue | Field |
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2004 | European Signal Processing Conference | Iterative reconstruction,Gradient method,Gradient descent,Deconvolution,Optics,Point spread function,Distortion,Gaussian function,Diffraction,Mathematics |
DocType | ISBN | Citations |
Conference | 978-320-0001-65-7 | 0 |
PageRank | References | Authors |
0.34 | 3 | 4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Daan Zhu | 1 | 5 | 0.83 |
Moe Razaz | 2 | 23 | 5.63 |
Andrew Hemmnings | 3 | 0 | 0.34 |
Binhai Wang | 4 | 4 | 2.55 |