Hyperuniform scalar random fields for lensless, multispectral imaging systems.

Area of Science:

• Optics and Photonics
• Pattern Formation Theory
• Computational Imaging

Background:

• Traditional lensless imaging systems face limitations in performance and resolution.
• Pattern formation theory offers novel approaches to designing optical components.
• Hyperuniform disordered systems exhibit unique statistical properties beneficial for imaging.

Purpose of the Study:

• To introduce a novel framework for designing lensless imaging systems.
• To develop new point-spread functions (PSFs) with enhanced isotropic behavior and controllable sparsity.
• To demonstrate improved image quality in lensless imaging applications.

Main Methods:

• Utilized hyperuniform random field solutions from nonlinear reaction-diffusion equations.
• Designed novel imaging PSFs and investigated their properties using modulated transfer functions.
• Developed a phase retrieval algorithm based on non-paraxial Rayleigh-Sommerfeld diffraction theory.
• Fabricated and tested hyperuniform phase plates (HPPs) for lensless imaging.

Main Results:

• Identified two-phase isotropic random fields with hyperuniform disorder as ideal for constructing imaging PSFs.
• Demonstrated superior performance of hyperuniform-based PSFs compared to Perlin noise-based PSFs.
• Achieved high-fidelity object reconstruction and improved image quality using engineered HPPs.
• Validated performance across the visible light spectrum.

Conclusions:

• The proposed framework enables systematic design of high-performance lensless imaging systems.
• Hyperuniform phase plates offer significant advantages for on-chip microscopy and spectroscopy.
• This work opens new avenues for advanced optical system design using pattern formation principles.