Compressed channeled spectropolarimetry

Abstract

Channeled spectropolarimetry measures the spectrally resolved Stokes parameters. A key aspect of this technique is to accurately reconstruct the Stokes parameters from a modulated measurement of the channeled spectropolarimeter. The state-of-the-art reconstruction algorithm uses the Fourier transform to extract the Stokes parameters from channels in the Fourier domain. While this approach is straightforward, it can be sensitive to noise and channel cross-talk, and it imposes bandwidth limitations that cut off high frequency details. To overcome these drawbacks, we present a reconstruction method called compressed channeled spectropolarimetry. In our proposed framework, reconstruction in channeled spectropolarimetry is an underdetermined problem, where we take N measurements and solve for 3N unknown Stokes parameters. We formulate an optimization problem by creating a mathematical model of the channeled spectropolarimeter with inspiration from compressed sensing. We show that our approach offers greater noise robustness and reconstruction accuracy compared with the Fourier transform technique in simulations and experimental measurements. By demonstrating more accurate reconstructions, we push performance to the native resolution of the sensor, allowing more information to be recovered from a single measurement of a channeled spectropolarimeter.

Silicon Channeled Spectropolarimeter for On‐Chip Single‐Detector Stokes Spectroscopy

“…In our optimization model, the cost function is defined as the deviation of the estimated channeled spectrum from the measured one and the outcome variables are wavelength‐dependent Stokes parameters. [ 14 ] As shown in Figure 6a, the estimated Stokes spectrum slowly closes to the input Stokes spectrum after each iteration. Details about the compressive sensing method are provided in Supplementary Note 2, Supporting Information.…”

“…Here, the signal‐to‐noise ratio (SNR) is defined by [ 14,35 ] where and are the optical intensity and white additive Gaussian noise, respectively, at the wavenumber . For the simulations of the RMSE varying with f , we set SNR at 25 dB according to our experimental results.…”

Snapshot polarized light scattering spectroscopy using spectrally‐modulated polarimetry for early gastric cancer detection

“…Traditionally, the FTM was used to extract the spectra of Stokes parameters in the Fourier frequency domain [35]. However, the recovered spectral resolution is usually three times lower than the intrinsic spectral resolution of the used spectrometer [37,39,45]. However, the accurate inference of the morphological information of cell nuclei requires the spectra of the single scattering light with a relatively high spectral resolution.…”

“…However, the state-of-the-art reconstruction method, Fourier transform method (FTM) [34][35][36][37][38], uses the Fourier transform to extract the Stokes parameters from the modulated spectrum in the frequency domain [35]. Although straightforward, FTM still has a series of problems such as channel cross-talk, highfrequency loss, and the need for phase calibration [37,[39][40][41], especially the reconstructed spectral resolution is lower than the used spectrometer, which makes the FTM unsuitable to the PLSS, and requires a relatively high spectral resolution. In order to overcome these problems, a novel reconstruction method called continuous slide iterative method (CSIM) was proposed by our group [39].…”

Chip-scale full-Stokes spectropolarimeter in silicon photonic circuits

“…Over the last decade, the demand for compact, cost-effective, and low-power spectropolarimeters has increased dramatically. Recently, some miniature architectures of such devices have been demonstrated [9][10][11][12]. However, these works were still exploring the possible improvements of traditional free-space optical components.…”