DiffuserCam: Lensless Single-exposure 3D Imaging

TL;DR

DiffuserCam is a simple, lensless 3D imaging system that captures volumetric data in a single shot using a diffuser and computational algorithms, enabling high-resolution 3D reconstructions from minimal hardware.

Contribution

This work introduces a novel lensless 3D imaging approach using a diffuser and efficient inverse algorithms, expanding the capabilities of computational cameras.

Findings

Reconstructed 100 million 3D voxels from a single 1.3 MP image.

Achieved high-resolution 3D imaging with a simple, compact setup.

Provided new theoretical analysis of resolution in computational cameras.

Abstract

We demonstrate a compact and easy-to-build computational camera for single-shot 3D imaging. Our lensless system consists solely of a diffuser placed in front of a standard image sensor. Every point within the volumetric field-of-view projects a unique pseudorandom pattern of caustics on the sensor. By using a physical approximation and simple calibration scheme, we solve the large-scale inverse problem in a computationally efficient way. The caustic patterns enable compressed sensing, which exploits sparsity in the sample to solve for more 3D voxels than pixels on the 2D sensor. Our 3D voxel grid is chosen to match the experimentally measured two-point optical resolution across the field-of-view, resulting in 100 million voxels being reconstructed from a single 1.3 megapixel image. However, the effective resolution varies significantly with scene content. Because this effect is common to a wide range of computational cameras, we provide new theory for analyzing resolution in such systems.