Methods for Removing Blurring Effects in X-ray Scattering and Diffraction Experiments

Abstract

The invention discloses a method for removing the blurring effect in X-ray scattering and diffraction experiments, which comprises the following steps: measuring the distribution of through-light spots on a two-dimensional detector to obtain h(x, y); measuring the scattering data of experimental samples to obtain g(x,y); respectively perform Fourier transform on h(x,y) and g(x,y) to obtain the distribution H(u,v) of the through spot in the reciprocal space and the distribution of the scattering data in the reciprocal space G(u,v); the experimental data H(u,v) and G(u,v) are deconvoluted by the Wiener filter algorithm, and the Fourier transform F of the data f(x,y) after the deblurring effect is obtained (u, v), perform inverse Fourier transform on F(u, v) to obtain the data f(x, y) after deblurring effect; adjust the parameter α according to the result of f(x, y) until the desired The deconvolution result. The present invention uses a Wiener filtering method to perform deconvolution processing on experimental data. Using this method improves the angular resolution of X-ray small-angle scattering data and improves the experimental precision.

Description

technical field [0001] The invention relates to the field of X-ray scattering and diffraction experiments, in particular to a method for removing blur effects in X-ray scattering and diffraction experiments. Background technique [0002] In X-ray scattering and diffraction experiments, the distribution of the beam and the point spread function of the detector will cause the experimental data to deviate from the ideal curve of the point light source, resulting in blurring effects. In order to combat this effect, it is proposed to deconvolute the data by means of Wiener filtering, so as to restore the ideal scattering diffraction data of point light sources. [0003] It is known from the X-ray scattering theory that a lot of structural information is contained in the angle data, and poor angular resolution will affect the accuracy of the experiment, and even get completely wrong results. There are two main factors that affect the angular resolution of two-dimensional data: on...

AI Technical Summary

Problems solved by technology

However, conventional direct deconvolution methods have certain limitations.

Mainly manifested in two aspects: 1. When the stretching function has a zero value in the entire detection interval, direct deconvolution is not available; 2. The direct deconvolution method is more sensitive to noise, and the noise of real data will affect the deconvolution. Convolution results have a big impact

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