Exploiting nonlinear incoherent image formation through linear volume metaoptics for inference

TL;DR

This paper demonstrates that nonlinear incoherent image formation through engineered linear volume metaoptics can encode and process 3D scenes, enabling novel inference capabilities in optical imaging.

Contribution

It introduces a method to encode 3D scene depth in the response function of linear volume metaoptics, exploiting nonlinear image formation for inference.

Findings

Depth maps are directly encoded in the optics response

Engineered dispersions create complex images from depth maps

Potential for nonlinear sensing of 3D scenes

Abstract

We showed that a 2D depth map representing an incoherent 3D opaque scene is directly encoded in the response function of an imaging optics. As a result, the optics creates an image that depends nonlinearly on the depth map. Furthermore, strong spatio-spectral dispersions in volume metaoptics can be engineered to create a complex image in response to a depth map. We hypothesize that this complexity will allow the linear volume metaoptics to nonlinearly sense and process 3D opaque scenes.