Abstract
Division-of-focal-plane (DoFP) polarization image sensors allow for snapshot imaging of linear polarization effects with inexpensive and straightforward setups. However, conventional interpolation based image reconstruction methods for such sensors
produce unreliable and noisy estimates of quantities such as degree of linear polarization (DoLP) or angle of linear polarization (AoLP). In this paper, we propose a polarization demosaicking algorithm by inverting the polarization image formation
model for both monochrome and color DoFP cameras. Compared to previous interpolation methods, our approach can significantly reduce noise induced artifacts and drastically increase the accuracy in estimating polarization states. We evaluate and
demonstrate the performance of the methods on a new high-resolution color polarization dataset. Simulation and experimental
results show that the proposed reconstruction and analysis tools offer an effective solution to polarization imaging
Original language | English (US) |
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Title of host publication | International Symposium on Vision, Modeling and Visualization, 2019 |
Publisher | The Eurographics Association |
ISBN (Print) | 978-3-03868-098-7 |
DOIs | |
State | Published - 2019 |
Bibliographical note
KAUST Repository Item: Exported on 2020-10-01Acknowledgements: This work was supported by King Abdullah University of Science and Technology as part of VCC center baseline funding and an equipment donation from LUCID Vision Labs. We thank Dr. Alex Tibbs for sharing data for initial test and Nadya Suvorova for helping dataset construction.
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Dive into the research topics of 'Polarization Demosaicking for Monochrome and Color Polarization Focal Plane Arrays'. Together they form a unique fingerprint.Datasets
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Polarization Image Dataset
Fu, Q. (Creator), Qiu, S. (Creator), Wang, C. (Creator), Heidrich, W. (Creator), Qiu, S. (Creator) & Qiu, S. (Creator), KAUST Research Repository, Feb 23 2020
DOI: 10.25781/KAUST-2VA2X, http://hdl.handle.net/10754/631914
Dataset