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Robustness of single random phase encoding lensless imaging with camera noise.

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    Coherent macroscopic single random phase encoding (SRPE) lensless imaging retains more information under camera noise than lens-based systems. This study analyzes noise robustness in SRPE systems, considering diffuser parameters for improved imaging with sensor noise.

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    Area of Science:

    • Optics and Photonics
    • Image Processing
    • Computational Imaging

    Background:

    • Lensless imaging techniques offer advantages in system compactness and cost.
    • Coherent macroscopic single random phase encoding (SRPE) is a promising lensless imaging modality.
    • Camera noise significantly impacts the performance and information fidelity of imaging systems.

    Purpose of the Study:

    • To assess the noise susceptibility of SRPE lensless imaging systems.
    • To quantify information loss in SRPE systems due to camera noise.
    • To compare the noise robustness of SRPE lensless imaging with traditional lens-based imaging.

    Main Methods:

    • Numerical simulations were performed to generate noise-free and noisy point spread functions (PSFs) for SRPE systems.
    • Shot noise, read noise, and quantization noise were introduced to simulate real-world camera noise.
    • Statistical measures were employed to quantify information content shared between noise-free and noisy PSFs.
    • Simulations were repeated with lenses replacing diffusers for comparative analysis.

    Main Results:

    • SRPE lensless imaging systems demonstrated superior information retention under high camera noise compared to lens-based systems.
    • The study identified key diffuser parameters (feature size, feature height variation) influencing SRPE system noise robustness.
    • Information loss was quantitatively correlated with increasing levels of camera noise.

    Conclusions:

    • SRPE lensless imaging exhibits enhanced robustness against camera noise, preserving more information than lens-based counterparts.
    • Diffuser characteristics play a critical role in optimizing the noise resilience of SRPE systems.
    • This research provides foundational insights for developing noise-resilient lensless SRPE imaging for applications with image sensor noise.