A Lensless Polarization Camera

2026-03-17

AI Summary

This work proposes a novel lensless polarimetric camera that overcomes the limitations of conventional polarization imaging systems, which typically rely on spatial or temporal multiplexing and suffer from bulky size, high cost, and structural complexity. By integrating a diffuser with a striped polarization mask in a single snapshot and employing a computational reconstruction algorithm that explicitly models polarization information, the system successfully recovers four-channel linear polarization images. This approach substantially simplifies the optical architecture while revealing key physical factors governing reconstruction quality. The study demonstrates the feasibility and potential of lensless designs for polarization imaging, offering a compact and efficient alternative to traditional systems.

Technology Category

• Computer Vision: Computational Photography, Image & Video Synthesis
• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Machine Learning: Multimodal Learning

Application Category

• Security and Privacy: Data transparency and provenance
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation

Abstract

Polarization imaging is a technique that creates a pixel map of the polarization state in a scene. Although invisible to the human eye, polarization can assist various sensing and computer vision tasks. Existing polarization cameras use spatial or temporal multiplexing, which increases the camera volume, weight, cost, or all of the above. Recent lensless imaging approaches, such as DiffuserCam, have demonstrated that compact imaging systems can be realized by replacing the lens with a coding element and performing computational reconstruction. In this work, we propose a compact lensless polarization camera composed of a diffuser and a simple striped polarization mask. By combining this optical design with a reconstruction algorithm that explicitly models the polarization-encoded lensless measurements, four linear polarization images are recovered from a single snapshot. Our results demonstrate the potential of lensless approaches for polarization imaging and reveal the physical factors that govern reconstruction quality, guiding the development of high-quality practical systems.

Problem

• polarization imaging
• lensless camera
• compact imaging
• polarization camera
• computational imaging

Innovation

• lensless imaging
• polarization camera
• computational reconstruction
• diffuser
• polarization mask