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Retrieval of Mouse Oocytes
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Phase retrieval with complexity guidance.

Mansi Butola, Sunaina Rajora, Kedar Khare

    Journal of the Optical Society of America. A, Optics, Image Science, and Vision
    |March 16, 2019
    PubMed
    Summary
    This summary is machine-generated.

    A new complexity-guided phase retrieval method overcomes stagnation artifacts common in iterative algorithms like Fienup. This approach ensures artifact-free solutions by guiding the phase retrieval process toward a target complexity value.

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    Area of Science:

    • Computational imaging
    • Image reconstruction
    • Digital signal processing

    Background:

    • Iterative phase retrieval algorithms, such as Gerchberg-Saxton (GS) and Fienup, often suffer from stagnation artifacts.
    • These artifacts hinder the accuracy and quality of the reconstructed phase information, even after extensive iterations.

    Purpose of the Study:

    • To introduce a novel complexity parameter (ζ) for quantifying phase retrieval solution fluctuations.
    • To develop a modified Fienup algorithm that mitigates stagnation artifacts using complexity guidance.
    • To achieve artifact-free phase retrieval solutions efficiently.

    Main Methods:

    • Introduced a complexity parameter (ζ) computable from Fourier magnitude data.
    • Developed a modified Fienup algorithm incorporating a controlled sparsity-enhancing step.
    • Ensured the complexity of the solution guess approaches ζ in each iteration (complexity-guided phase retrieval).

    Main Results:

    • The complexity of standard Fienup solutions with artifacts stabilizes at a value higher than ζ.
    • Complexity-guided phase retrieval successfully produced artifact-free solutions within a few hundred iterations.
    • Demonstrated effectiveness for both amplitude and phase objects, with and without Poisson noise.

    Conclusions:

    • Complexity-guided phase retrieval offers an effective strategy to overcome stagnation artifacts in iterative methods.
    • The introduced complexity parameter provides a valuable metric for assessing phase retrieval quality.
    • This approach holds potential for integration with various phase retrieval algorithms and practical applications.