Self-calibration for a spatially modulated snapshot Mueller matrix imaging polarimeter.

The self-calibration technique based on a spatially modulated snapshot Mueller matrix imaging polarimeter is proposed in this paper. Taking the snapshot Mueller matrix imaging polarimeter using modified Savart polariscopes as an example, it demonstrates that the self-calibration method can utilize frequency-domain information from independent channels to determine the spatial carrier frequency, thereby achieving frequency-domain filtering and demodulation instead of the traditional reference light calibration. This eliminates the inaccuracies introduced by the imprecise measurement of reference lights and environmental changes in the traditional calibration method, simplifies the experimental process, and removes biases caused by manual operations. The optical system design consists of two parts: the polarization state generator and the polarization state analyzer. Through the modulation of modified Savart polariscopes and half-wave plates, spatially separated interference fringes are generated. The modulation process employing Fourier transforms to the intensity of interference fringes yields 49 independent channels. Then, the demodulation process employing inverse Fourier transforms and subsequent mathematical operations on the information from each channel enables the reconstruction of 16 Mueller matrix elements. Theoretical analysis demonstrates that the system can accurately reconstruct the target's Mueller matrix using self-calibration algorithms, and its feasibility is validated through numerical simulation experiments. Experimental results show that the structural similarity index between the reconstructed images and the input target images exceeds 0.9, attaining favorable reconstruction outcomes. This technique provides a high-resolution, low-bias calibration solution for a spatially modulated snapshot Mueller matrix imaging polarimeter without using external reference lights. It holds significant application potential in biomedical science, materials research, remote sensing, and related fields.