Diffraction-unlimited imaging based on conventional optical devices

Nicolas Ducros,Aurélien Bourquard

doi:10.1364/oe.388084

Abstract

We propose a computational paradigm where off-the-shelf optical devices can be used to image objects in a scene well beyond their native optical resolution. By design, our approach is generic, does not require active illumination, and is applicable to several types of optical devices. It only requires the placement of a spatial light modulator some distance from the optical system. In this paper, we first introduce the acquisition strategy together with the reconstruction framework. We then conduct practical experiments with a webcam that confirm that this approach can image objects with substantially enhanced spatial resolution compared to the performance of the native optical device. We finally discuss potential applications, current limitations, and future research directions.

Highlights

The resolution of an imaging system, i.e., its ability to separate points that are located at small angular positions, is limited by the density of the sensors and by diffraction
A practical implementation of compressed sensing is seen in the single-pixel camera, where a scene is imaged based on a single detector [3]
We evaluate this approach considering a webcam (USB HD C270; Logitech) as the conventional optical device (Fig. 3(a)) and the front screen of a commercial showcase (ClearVue Lite CV101LV1) as the spatial light modulator (SLM) (Fig. 3(b))

Summary

Introduction

The resolution of an imaging system, i.e., its ability to separate points that are located at small angular positions, is limited by the density of the sensors and by diffraction. Applications of single-pixel imaging include microscopy [4], terahertz imaging [5], fluorescence lifetime imaging [6], time-resolved hyperspectral imaging [7], Raman imaging [8], and phase imaging [9]—see [10] for a recent review. In parallel to this trend, the spatial density of sensors has increased substantially, with native camera resolutions in standard mobile phones exceeding ten megapixels. In most consumer and professional optical devices, computational methods that compensate for a lack of sensors are not critical

Objectives

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Discussion

Conclusion