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    Area of Science:

    • Optics and Photonics
    • Image Reconstruction
    • Diffraction Imaging

    Background:

    • Multiplane iterative phase retrieval is crucial for determining object characteristics.
    • Limited dynamic range in detection systems leads to overexposure and data loss.
    • Existing methods struggle with saturated intensity distributions in diffraction imaging.

    Purpose of the Study:

    • To develop a novel reconstruction algorithm for diffraction imaging.
    • To address the challenge of overexposed intensity data caused by limited dynamic range.
    • To reliably retrieve complex wave amplitude from saturated datasets.

    Main Methods:

    • A new reconstruction algorithm employing inpainting for saturated areas.
    • Testing the algorithm in the terahertz frequency range.
    • Comparison with high dynamic range techniques for validation.

    Main Results:

    • The algorithm successfully inpaints saturated regions in intensity datasets.
    • Retrieved amplitude and phase distributions match the quality of high dynamic range methods.
    • The technique was validated in the terahertz frequency range.

    Conclusions:

    • The proposed inpainting algorithm significantly improves diffraction imaging with limited dynamic range detectors.
    • This method simplifies data acquisition and expands possibilities for designing measurement tools.
    • The approach is applicable across various spectral ranges, particularly beneficial in the terahertz domain.