Snapshot polarimetry relies on the micro-polarizer array (MPA)—a spatial multiplexing of pixel-sized wiregrid analyzers. The limitation of MPA-based polarimetric imaging is the loss of spatial resolution and light received by each pixel. Reconstructing the degree and the angle of linear polarization (DoLP and AoLP, respectively) from MPA accurately requires the joint application of demosaicking (to demodulate the spatial modulation of the wiregrid analyzers) and denoising (to account for photon and thermal noise). We propose a wavelet-based Bayesian estimation technique for jointly demosaicking and denoising 2 × 2 MPA-sampled sensor data.
In 2014, we laid out the theory for how a 2×4 microgrid polarimetric array provides superior spatial resolution when compared to a conventional 2×2 array. In this paper, we provide experimental evidence to support our claims via a prototype 2×4-patterned infrared microbolometer camera developed by Polaris Sensors Technologies. The benefits of the 2×4 array are obtained through a combination of the physical arrangement of the pattern itself and though the application of a log-based framework for reconstructing degree and angle of linear polarization directly, without calculating Stokes parameters or interpolating intensity channels as intermediate steps.
In polarimetric imaging, degree and angle of linear polarization (DoLP and AoLP, respectively) are computed from ratios of Stokes parameters. In snapshot imagers, however, DoLP and AoLP are degraded by inherent mismatches between the spatial bandwidth supports of S0, S1, and S2 parameters reconstructed by demosaicking from microgrid polarizer array (MPA)-sampled data. To overcome this shortcoming, we rigorously show that log-MPA-sampled data approximately decouples DoLP and AoLP from the intensity component (S0) in the spatial Fourier domain. Based on this analysis, we propose an alternative demosaicking strategy aimed at estimating DoLP and AoLP directly from MPA-sampled data. Our method bypasses Stokes parameter estimation, alleviating the spatial bandwidth mismatch problems altogether and reducing the computational complexity. We experimentally verify the superior DoLP and AoLP reconstructions of the proposed log-MPA demosaicking compared to the conventional Stokes parameter demosaicking approach in simulation. We simulated the conventional 2 × 2 MPA patterns as well as the more recently introduced 2 × 4 MPA patterns, and report quantitative (mean squared error, structural similarity index, and polarization angular error) and qualitative results. We also provide a closed-form approximation error analysis on the log-MPA-sampled data to demonstrate that the approximation error is negligible for real practical applications.
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