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Efficient implementation of the Shack-Hartmann centroid extraction for edge computing.

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    Summary
    This summary is machine-generated.

    We developed an efficient Shack-Hartmann wavefront sensor algorithm for edge computing, achieving sub-2 ms latency for centroid extraction. This optimized approach is suitable for real-time adaptive optics systems.

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    Area of Science:

    • Optics and Photonics
    • Computer Engineering
    • Embedded Systems

    Background:

    • Adaptive optics (AO) systems correct optical aberrations in real-time.
    • Wavefront sensors (WFS), particularly Shack-Hartmann (SH) sensors, are crucial for measuring these aberrations.
    • Edge computing requires efficient algorithms for low-latency data processing on embedded hardware.

    Purpose of the Study:

    • To propose an efficient centroid extraction algorithm for Shack-Hartmann wavefront sensors.
    • To optimize the algorithm for edge computing environments with unified CPU/GPU memory.
    • To meet the low-latency requirements of adaptive optics control loops.

    Main Methods:

    • Implemented an optimized centroid extraction algorithm for SH-WFS.
    • Leveraged unified CPU/GPU memory architectures in low-power embedded systems.
    • Tested the algorithm on spot images up to 700x700 pixels.

    Main Results:

    • Achieved centroid extraction latency below 2 milliseconds.
    • Demonstrated the algorithm's efficiency on embedded platforms.
    • Validated the approach for real-time AO applications.

    Conclusions:

    • The proposed SH-WFS centroid extraction algorithm is efficient for edge computing.
    • The sub-2 ms latency meets the temporal demands of small-to-medium AO systems.
    • This method enables faster aberration correction in AO systems with limited actuators.