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Deconvolution of the two-dimensional point-spread function of area detectors using the maximum-entropy algorithm

机译:使用最大熵算法对区域探测器的二维点扩展函数进行反卷积

摘要

The maximum-entropy method (MEM) has been applied for the deconvolution of the point-spread function (PSF) of two-dimensional X-ray detectors. The method is robust, model and image independent, and only depends on the correct description of the two-dimensional point-spread function and gain factor of the detector. A significant enhancement of both the spatial resolution and the contrast ratio has been obtained for two phase-contrast images recorded with an ultra-high-resolution X-ray imaging detector. The method has also been applied to a Laue diffraction image of a protein crystal, showing an important improvement in both the peak separation of closely spaced diffraction peaks and the signal-to-noise ratio of medium and weak peaks. The principle of the method is explained and examples of its application are presented.
机译:最大熵方法(MEM)已应用于二维X射线探测器的点扩展函数(PSF)的反卷积。该方法是鲁棒的,模型和图像无关的,并且仅取决于对二维点扩展函数和检测器的增益因子的正确描述。对于使用超高分辨率X射线成像检测器记录的两个相位对比图像,已经获得了空间分辨率和对比度的显着提高。该方法也已应用于蛋白质晶体的劳厄(Laue)衍射图像,显示出在紧密排列的衍射峰的峰分离以及中峰和弱峰的信噪比方面都得到了重要的改进。解释了该方法的原理,并给出了其应用示例。

著录项

  • 作者

    Graafsma H; de Vries R.Y.;

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  • 年度 1999
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