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    Area of Science:

    • Optical Engineering
    • Image Processing
    • Infrared Optics

    Background:

    • Diffractive optical elements (DOEs) exhibit negative dispersion, challenging infrared minimalist optical systems.
    • Large-aperture hybrid-order monolithic imaging diffractive (HMID) lenses suffer from processing errors and aberrations, degrading image quality.
    • Traditional aberration correction methods, like adding extra lenses, contradict the minimalist design goal.

    Purpose of the Study:

    • To propose a joint optical-algorithmic processing method to improve image quality in large-aperture HMID lenses.
    • To enhance the performance of minimalist infrared optical systems.
    • To provide a framework for using monolithic imaging systems in large-aperture applications.

    Main Methods:

    • Designed an Upgraded HMID (UHMID) by fine-tuning microstructure height to improve Strehl ratio (SR).
    • Developed a denoiser using Bayesian theory and a deep neural network.
    • Utilized optical system point spread function (PSF) data for image restoration.

    Main Results:

    • The UHMID design improved image quality through Strehl ratio enhancement.
    • Image restoration using the proposed method significantly increased resolution.
    • Experimental results showed a resolution increase from 21.13 lp/mm to 31.33 lp/mm (48.27% improvement).

    Conclusions:

    • The joint optical-algorithmic approach effectively addresses aberrations and processing errors in large-aperture HMID lenses.
    • The developed method enhances image resolution and quality in infrared minimalist optical systems.
    • This principle offers a viable framework for employing monolithic imaging systems in demanding large-aperture optical applications.