Efficient acquisition of Mueller matrix via spatially modulated polarimetry at low light field.

Mueller polarimetry performed in low light field with high speed and accuracy is important for the diagnosis of living biological tissues. However, efficient acquisition of the Mueller matrix at low light field is challenging owing to the interference of background-noise. In this study, a spatially modulated Mueller polarimeter (SMMP) induced by a zero-order vortex quarter wave retarder is first presented to acquire the Mueller matrix rapidly using only four camera shots rather than 16 shots, as in the state of the art technique. In addition, a momentum gradient ascent algorithm is proposed to accelerate the reconstruction of the Mueller matrix. Subsequently, a novel adaptive hard thresholding filter combined with the spatial distribution characteristics of photons at different low light levels, in addition to a low-pass fast-Fourier-transform filter, is utilized to remove redundant background noise from raw-low intensity distributions. The experimental results illustrate that the proposed method is more robust to noise perturbation, and its precision is almost an order of magnitude higher than that of the classical dual-rotating retarder Mueller polarimetry at low light field.

High-accuracy reconstruction of Stokes vectors via spatially modulated polarimetry using deep learning at low light field.

Polarization measurement is generally performed in scenes with a low signal-to-noise ratio (SNR) such as remote sensing and biological tissue detection. The spatially modulated polarimeter can satisfy the real-time measurement requirements in low SNR scenes by establishing the mapping between photon spatial distribution and polarization information. However, accurately measuring the polarization state under low-light illumination becomes highly challenging owing to the interference of background noise. In this paper, a deep learning method is proposed and applied to the high-accuracy reconstruction of polarization information at low light field. A reinforced two-layer deep convolutional neural network is designed to respectively extract global and local features of noise in this method. Accurate photon spatial distribution can be obtained by fusing and processing these features. Experimental results illustrate the excellent accuracy achieved by the proposed method with a maximum average value of the absolute measured error below 0.04. More importantly, the proposed method is well-performed for the reconstruction of Stokes vectors at low light fields of various levels without requiring changes to the model, enhancing its practicality and simplicity.

Optimal design for a broadband Stokes polarimeter of liquid crystal variable retarders.

Liquid crystal variable retarders (LCVRs) are the core component for rapid and high-precision broadband polarization detection. Additionally, the ability to suppress noise greatly affects the results of polarization measurements. In this work, a solving optimal design approach is proposed for building a high-performance broadband Stokes polarimeter based on LCVRs, which greatly reduces the influences of data fluctuation from liquid crystals and dispersion on the experimental results. This method relies on evaluation criteria of the condition number (CN) to build a gradual optimization that includes the following three steps: fixing the fast axis angles, meeting the requirements of a wideband, and ensuring a minimum CN. Additionally, with the method of increasing the measurement analysis vector, we ensure the whole band in the low CN and offer a solution to the problem of the difficulty in optimizing the LCVRs caused by the large change of retardance at 490-700 nm. Finally, the rapid and high-precision Stokes measurement of 490-700 nm wavelengths is achieved. We test the performance of the polarimeter after optimization in our simulation and experiment, which shows that the total RMS error is less than 0.032 and the single point error is small. This work not only reduces the influence of LCVR error on the experimental results but also makes it possible to apply LCVRs to 490-700 nm detection.

Optimized spatially modulated polarimetry with an efficient calibration method and hybrid gradient descent reconstruction.

High accuracy and fast polarization measurements at a low light field are significant in various applications, spanning from quantum optics to diagnosis of living biological tissue. In this paper, we developed an optimized spatially modulated polarimetry (OSMP) with an efficient calibration method that establishes a quantitative link between the intensity distribution of an arbitrary incident polarization state and four intensity distributions of specific input polarization states. Such a calibration method not only considers the total polarimetric errors induced by polarization elements and the focusing lens but also simplifies the procedure of calibration. A hybrid gradient descent (HGD) algorithm, combining the rapidity of optimization of gradient descent (GD) algorithm and the accuracy of optimization of direct enumeration (DE) algorithm, was proposed to restructure the Stokes parameters. Experiment results illustrate that the proposed method can significantly improve the speed and accuracy of polarization measurements over existing spatially modulated polarimeters based on the vortex wave retarder, whether in strong or low light fields.

Holistic and efficient calibration method for Mueller matrix imaging polarimeter with a high numerical aperture.

High-numerical aperture (N A>0.6) Mueller matrix imaging polarimeter (MMIP) (high-NA MMIP) is urgently needed for higher resolution. Usually, the working distance of high-NA MMIP is too short to perform in situ calibration by a usual reference sample, such as polarizer and retarder plates. The polarization effects of the substrate that attach the sample are never calibrated. So, the resolution and accuracy of the MMIP is hard to further promote. In this paper, a holistic and efficient calibration method is innovated for high-NA MMIP. Two film polarizers and a film retarder as well as a blank substrate are first adopted as the reference samples in calibration. Different from the conventional eigenvalue calibration method (ECM), the holistic calibration theory and process are established. All polarimetric errors arising from the devices, subsystems, and the substrate can be calibrated in one process. The normalized measurement error is less than 0.0024 for NA 0.95 MMIP, which is an order of magnitude lower than those of NA 0.1 and 0.2 MMIPs in publications. The excellent performance of calibrated high-NA MMIP is demonstrated by tissue polarimetry with higher resolution, accuracy, and more appropriate dynamic range.