Single-shot Sub-Rayleigh Imaging with Sparse Detection

TL;DR

This paper demonstrates a method for achieving imaging resolution beyond the Rayleigh limit by using single-shot thermal illumination and sparse-array single-pixel detectors, leveraging prior sparsity knowledge.

Contribution

It introduces a novel sub-Rayleigh imaging technique combining sparse detection and prior object sparsity, validated through simulations and experiments.

Findings

Sub-Rayleigh resolution achieved with sparse detection.

Imaging quality depends on number of detectors and SNR.

Method surpasses conventional Rayleigh limit constraints.

Abstract

For conventional imaging, the imaging resolution limit is given by the Rayleigh criterion. Exploiting the prior knowledge of imaging object's sparsity and fixed optical system, imaging beyond the conventional Rayleigh limit, which is backed up by numerical simulation and experiments, is achieved by illuminating the object with single-shot thermal light and detecting the object's information at the imaging plane with some sparse-array single-pixel detectors. The quality of sub-Rayleigh imaging with sparse detection is also shown to be related to the effective number of single-pixel detectors and the detection signal-to-noise ratio at the imaging plane.