PIDSR: Complementary Polarized Image Demosaicing and Super-Resolution
Shuangfan Zhou, Chu Zhou, Youwei Lyu, Heng Guo, Zhanyu Ma, Boxin Shi, Imari Sato
Abstract
Polarization cameras can capture multiple polarized images with different polarizer angles in a single shot, bringing convenience to polarization-based downstream tasks. However, their direct outputs are color-polarization filter array (CPFA) raw images, requiring demosaicing to reconstruct full-resolution, full-color polarized images; unfortunately, this necessary step introduces artifacts that make polarization-related parameters such as the degree of polarization (DoP) and angle of polarization (AoP) prone to error. Besides, limited by the hardware design, the resolution of a polarization camera is often much lower than that of a conventional RGB camera. Existing polarized image demosaicing (PID) methods are limited in that they cannot enhance resolution, while polarized image super-resolution (PISR) methods, though designed to obtain high-resolution (HR) polarized images from the demosaicing results, tend to retain or even amplify errors in the DoP and AoP introduced by demosaicing artifacts. In this paper, we propose PIDSR, a joint framework that performs complementary Polarized Image Demosaicing and Super-Resolution, showing the ability to robustly obtain high-quality HR polarized images with more accurate DoP and AoP from a CPFA raw image in a direct manner. Experiments show our PIDSR not only achieves state-of-the-art performance on both synthetic and real data, but also facilitates downstream tasks.
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Cited by top-tier papers2
- Polarimetric Neural Field via Unified Complex-Valued Wave RepresentationChu Zhou, Yixin Yang, Junda Liao, Heng Guo et al.ICCV 2025 · 1 citation
- Polarization Uncertainty-Guided Diffusion Model for Color Polarization Image DemosaickingChenggong Li, Yidong Luo, Junchao Zhang, Degui YangAAAI 2026
Builds on6
- Restormer: Efficient Transformer for High-Resolution Image RestorationSyed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat et al.CVPR 2022 · 3,348 citations
- SinSR: Diffusion-Based Image Super-Resolution in a Single StepYufei Wang, Wenhan Yang, Xinyuan Chen, Yaohui Wang et al.CVPR 2024 · 110 citations
- Learning to dehaze with polarizationChu Zhou, Minggui Teng, Yufei Han, Chao Xu et al.NeurIPS 2021 · 72 citations
- Polarization-Aware Low-Light Image EnhancementChu Zhou, Minggui Teng, Youwei Lyu, Si Li et al.AAAI 2023 · 33 citations
- Implicit Diffusion Models for Continuous Super-ResolutionSicheng Gao, Xuhui Liu, Bohan Zeng, Sheng Xu et al.CVPR 2023
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