| Title | Polarized Intensity Ratio Constraint Demosaicing for the Division of a Focal-Plane Polarimetric Image |
| Authors | Yan, Lei Jiang, Kaiwen Lin, Yi Zhao, Hongying Zhang, Ruihua Zeng, Fangang |
| Affiliation | Guilin Univ Aerosp Technol, Guangxi Key Lab UAV Remote Sensing, Guilin 541004, Peoples R China Peking Univ, Inst Remote Sensing & Geog Informat Syst, Spatial Informat Integrat & 3S Engn Applicat Beij, Beijing 100871, Peoples R China Renmin Univ China, Sch Environm Nat Resources, Beijing 100872, Peoples R China |
| Keywords | RESIDUAL INTERPOLATION SPARSE REPRESENTATION NETWORK |
| Issue Date | Jul-2022 |
| Publisher | REMOTE SENSING |
| Abstract | Polarization is an independent dimension of light wave information that has broad application prospects in machine vision and remote sensing tasks. Polarization imaging using a division-of-focal-plane (DoFP) polarimetric sensor can meet lightweight and real-time application requirements. Similar to Bayer filter-based color imaging, demosaicing is a basic and important processing step in DoFP polarization imaging. Due to the differences in the physical properties of polarization and the color of light waves, the widely studied color demosaicing method cannot be directly applied to polarization demosaicing. We propose a polarized intensity ratio constraint demosaicing model to efficiently account for the characteristics of polarization detection in this work. First, we discuss the special constraint relationship between the polarization channels. It can be simply described as: for a beam of light, the sum of the intensities detected by any two vertical ideal analyzers should be equal to the total light intensity. Then, based on this constraint relationship and drawing on the concept of guided filtering, a new polarization demosaicing method is developed. A method to directly use raw images captured by the DoFP detector as the ground truth for comparison experiments is then constructed to aid in the convenient collection of experimental data and extensive image scenarios. Results of both qualitative and quantitative experiments illustrate that our method is an effective and practical method to faithfully recover the full polarization information of each pixel from a single mosaic input image. |
| URI | http://hdl.handle.net/20.500.11897/649781 |
| DOI | 10.3390/rs14143268 |
| Indexed | SCI(E) |
| Appears in Collections: | 地球与空间科学学院 空间信息集成与3S工程应用北京市重点实验室 |
