High-Resolution Single-Shot Polarimetric Imaging Made Easy

📅 2026-04-07
📈 Citations: 0
Influential: 0
📄 PDF
🤖 AI Summary
Division-of-Focal-Plane (DoFP) polarimetric imaging suffers from reduced spatial resolution and artifact generation due to its single-shot acquisition scheme. To address these limitations, this work proposes EasyPolar, a multi-view polarimetric imaging framework that integrates, for the first time, a three-camera synchronized capture system—comprising one unpolarized and two orthogonally polarized views—with a physics-guided confidence-based fusion mechanism. By leveraging multimodal feature fusion, a confidence-guided reconstruction network, and geometric constraint optimization, the proposed method preserves the advantage of single-shot acquisition while effectively overcoming the inherent resolution and artifact constraints of DoFP sensors. This approach significantly enhances polarization image quality and improves performance in downstream vision tasks.
📝 Abstract
Polarization-based vision has gained increasing attention for providing richer physical cues beyond RGB images. While achieving single-shot capture is highly desirable for practical applications, existing Division-of-Focal-Plane (DoFP) sensors inherently suffer from reduced spatial resolution and artifacts due to their spatial multiplexing mechanism. To overcome these limitations without sacrificing the snapshot capability, we propose EasyPolar, a multi-view polarimetric imaging framework. Our system is grounded in the physical insight that three independent intensity measurements are sufficient to fully characterize linear polarization. Guided by this, we design a triple-camera setup consisting of three synchronized RGB cameras that capture one unpolarized view and two polarized views with distinct orientations. Building upon this hardware design, we further propose a confidence-guided polarization reconstruction network to address the potential misalignment in multi-view fusion. The network performs multi-modal feature fusion under a confidence-aware physical guidance mechanism, which effectively suppresses warping-induced artifacts and enforces explicit geometric constraints on the solution space. Experimental results demonstrate that our method achieves high-quality results and benefits various downstream tasks.
Problem

Research questions and friction points this paper is trying to address.

polarimetric imaging
single-shot
spatial resolution
artifacts
Division-of-Focal-Plane
Innovation

Methods, ideas, or system contributions that make the work stand out.

single-shot polarimetric imaging
multi-view fusion
confidence-guided reconstruction
high-resolution polarization
physical guidance
🔎 Similar Papers
No similar papers found.
S
Shuangfan Zhou
School of Artificial Intelligence, Beijing University of Posts and Telecommunications, China
Chu Zhou
Chu Zhou
National Institute of Informatics
Computational Photography
Heng Guo
Heng Guo
Beijing University of Posts and Telecommunications
computer vision
Y
Youwei Lyu
School of Artificial Intelligence, Beijing University of Posts and Telecommunications, China
Boxin Shi
Boxin Shi
Peking University
Computer VisionComputational Photography
Zhanyu Ma
Zhanyu Ma
Beijing University of Posts and Telecommunications
Pattern RecognitionMachine LearningComputer VisionMultimedia TechnologyDeep Learning
I
Imari Sato
National Institute of Informatics, Japan