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The size of the unit cell and the arrangement of atoms in a crystal may be determined from measurements of the diffraction of X-rays by the crystal, termed X-ray crystallography.
Diffraction
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X-ray diffraction or XRD is an analytical tool that utilizes X-rays to study ordered structures such as crystalline organic and inorganic samples, polycrystalline materials, proteins, carbohydrates, and drugs.
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Related Experiment Video

Updated: Feb 19, 2026

Measuring Spatially- and Directionally-varying Light Scattering from Biological Material
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Measuring Spatially- and Directionally-varying Light Scattering from Biological Material

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Diffraction effects detection for HDR image-based measurements.

A Lucat, R Hegedus, R Pacanowski

    Optics Express
    |November 3, 2017
    PubMed
    Summary
    This summary is machine-generated.

    This study presents a new algorithm to remove star-burst patterns caused by diffraction in high dynamic range (HDR) images. The method accurately identifies and discards affected pixels, improving measurement reliability.

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    Area of Science:

    • Optics and Photonics
    • Image Processing
    • Computational Imaging

    Background:

    • High dynamic range (HDR) imaging captures scenes with a wide range of light intensities.
    • Camera aperture diffraction creates star-burst patterns around bright highlights in HDR images.
    • These diffraction artifacts corrupt pixel data, compromising measurement accuracy.

    Purpose of the Study:

    • To develop a novel algorithm for mitigating diffraction artifacts in HDR images.
    • To accurately predict and remove star-burst patterns affecting pixel measurements.
    • To improve the reliability of data obtained from HDR imaging.

    Main Methods:

    • A closed-form Point Spread Function (PSF) is utilized to model diffraction effects.
    • The algorithm predicts the spatial extent of diffraction-induced pixel alterations.
    • Affected pixels are identified and excluded from subsequent measurements.

    Main Results:

    • The proposed algorithm effectively identifies and discards pixels affected by diffraction.
    • It outperforms conventional deconvolution techniques in artifact removal.
    • The method successfully recovers uncertainty values, including convolution kernel and noise.

    Conclusions:

    • The novel algorithm enhances the reliability of HDR image measurements by addressing diffraction artifacts.
    • It offers a more accurate solution compared to existing deconvolution methods.
    • This technique is valuable for applications requiring precise photometric measurements from HDR images.