Coded Illumination for 3D Lensless Imaging

TL;DR

This paper introduces a method using coded illumination and spatial baseline to enhance 3D reconstruction in lensless cameras, significantly improving depth and spatial resolution through multiple measurements and system design.

Contribution

It proposes a novel approach combining coded illumination patterns and baseline positioning to improve 3D imaging resolution in lensless systems.

Findings

Enhanced 3D reconstruction quality demonstrated in simulations.

Experimental validation with a prototype confirms effectiveness.

Improved depth resolution due to distinguishable PSFs across depths.

Abstract

Mask-based lensless cameras offer a novel design for imaging systems by replacing the lens in a conventional camera with a layer of coded mask. Each pixel of the lensless camera encodes the information of the entire 3D scene. Existing methods for 3D reconstruction from lensless measurements suffer from poor spatial and depth resolution. This is partially due to the system ill conditioning that arises because the point-spread functions (PSFs) from different depth planes are very similar. In this paper, we propose to capture multiple measurements of the scene under a sequence of coded illumination patterns to improve the 3D image reconstruction quality. In addition, we put the illumination source at a distance away from the camera. With such baseline distance between the lensless camera and illumination source, the camera observes a slice of the 3D volume, and the PSF of each depth plane becomes more resolvable from each other. We present simulation results along with experimental results with a camera prototype to demonstrate the effectiveness of our approach.