This study presents a complete Mueller matrix imaging polarimeter which speeds up the pixel-wise recovery of the Mueller matrix of the scene. Our system allows us to acquire the Mueller matrix in a large field of view using white light in only 4 acquisitions. The camera is based on a division of aperture scheme that allows obtaining four sub-images on the sensor surface, decreasing the typical time of the measurement. The polarization states that analyse the input polarization are optimized to immunize the polarimeter to Gaussian and Poisson noise during the acquisitions. The results show the system can measure the complete Mueller matrix in broadband with errors lower than 10% at each component.
In recent times, there has been a surge of interest in LiDAR imaging systems, particularly in outdoor terrestrial applications associated with computer vision. However, a significant hurdle preventing their widespread implementation lies in their limited tolerance for adverse weather conditions, such as fog. To address this challenge, researchers have explored the capability of polarization in improving detection capabilities in such media. This paper explores the potential of LiDAR technology to obtain polarized images through fog and investigates the impact of fog on object detection using digitized temporal signals and point clouds. The study utilizes a LiDAR-polarized imaging system using circular polarization, which has been shown to enhance image contrast in highly-dispersive media. The analysis of the polarimetric information of the backscattered light signal in fog reveals its influence on object detection and evaluates the range difference between orthogonal polarimetric channels: coplanar and cross-configuration. The results demonstrate that cross-configuration detection provides larger range and more detailed point clouds compared to co-planar configuration, particularly benefiting metallic objects, for the same foggy conditions. By utilizing circularly polarized incident light and cross-configuration detection, the LiDAR system can improve the signal-to-noise ratio by filtering out the co-polarized fog responses. However, the range of the system may be reduced compared to non-polarized detection. Overall, our findings indicate that utilizing a cross-polarization detection setup can effectively reduce the impact of fog backscatter while preserving the return signal from objects of interest in the majority of cases.
This contribution explains the development of a full-Stokes imaging polarimeter that provides the 2D map of the polarization state of a scene in a single acquisition working in the complete visible band. The nature of polarization makes it impossible to measure it using a single measurement with bare intensity-based detectors. Stokes parameters describe the state of polarization of light and provide the amplitudes of the electric field and the phase difference of the two components orthogonal to propagation using simple experiments that measure the time-averaged intensity of the waves. Our camera can transform the input polarization into intensity by using polarization-sensitive elements to recover the complete Stokes vector at each pixel of the camera. The states used for measuring the input polarization are claimed to be the optimal polarization states allowing for fast acquisition in a single shot while keeping the acquisition immunized to Gaussian and Poisson noise. The acquisition errors for full-Stokes parameters are demonstrated to be lower than 10% showing the capability of the system to perform Stokes imaging both in indoor and outdoor scenes. The camera has great potential in computer vision and deep learning applications due to the complementarity of the information provided when compared to intensity data
Nowadays, taking advantage of polarization allows enhancing the contrast of a detected object and extending the information of the scene compared to conventional intensity imagery, as the information added by polarimetric images is complementary to intensity ones. Using polarization has a wide interest in space exploration, earth remote sensing, machine vision and biomedical diagnosis, and is extending its use to several applications. Here, we present a basic imaging polarimeter which measures the full Stokes vector of the scene based on a division of time structure, based on a consumer CMOS camera. The polarization state of partially or fully polarized light can be represented by means of the Stokes vector, which is the goal of the measurement. However, due to its nature, the components of the Stokes vector cannot be measured directly, as they must be recovered from a set of intensity measurements. In the paper the results show the measured intensity at 632nm and the recovered Stokes data produced by the determined data reduction matrix at six reference polarization states, as well as the theoretical and recovered Stokes parameters from the calibration experiment. The root mean square (RMS) errors are below 10% . Therefore, this system can provide a well-conditioned data reduction matrix for noise immunity and the spectral range can be widened by using white light and a monochrome camera.
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