Achromatic Full Stokes Polarimetry Metasurface for Full-Color Polarization Imaging in the Visible Range.

Metasurfaces provide an ultrathin platform for compact, real-time polarimetry. However, their applications in polychromatic scenes are restricted by narrow operating bandwidths that causes spectral information loss. Here, we demonstrate full-color polarization imaging using an achromatic polarimeter consisting of four polarization-dependent metalenses. Leveraging an intelligent design scheme, we achieve effective arbitrary phase compensation and multiobjective matching with a limited database. This system provides broadband achromaticity across wavelengths from 450 to 650 nm, resulting in a relative bandwidth of approximately 0.364 for full Stokes imaging. Experimental reconstruction errors for wavelengths of 450, 550, and 650 nm are 7.5%, 5.9%, and 3.8%, respectively. Performance is evaluated based on both achromatic bandwidth and crosstalk, with our design achieving three times the performance of the current state-of-the-art. The full-color, full-polarization imaging capability of the device is further validated with a customized object. The proposed scheme advances polarization imaging for practical applications.

A New Method for Ground-Based Optical Polarization Observation of the Moon.

As a natural satellite of the Earth, the moon is a prime target for planetary remote sensing exploration. However, lunar polarization studies are not popular in the planetary science community. Polarimetry of the lunar surface had not been carried out from a spacecraft until the Korean lunar exploration program was initiated. In previous polarization observations of the moon, images of different polarization states were obtained by a rotating linear polarizer. This method is not well suited for future polarization observations from space-based spacecraft. To this end, we present a new kind of polarized observation of the moon using a division of a focal-plane polarization camera and propose a pipeline on the processing method of the polarization observation of the moon. We obtain a map of the degree of white-light polarization on the nearside of the moon through polarization observation, data processing, and correction. The observation and data processing methods presented in this study have the potential to serve as a reference for analyzing polarization observation data from future orbiting spacecraft. These are expected to lead to new discoveries in the fields of astronomy and planetary science.

Imaging technologies for presurgical margin assessment of basal cell carcinoma.

Basal cell carcinoma is the most common cancer worldwide, necessitating the development of techniques to decrease treatment costs through efficiency and efficacy. Mohs micrographic surgery, a specialized surgical technique involving staged resection of the tumor with complete histologic evaluation of the peripheral margins, is highly utilized. Reducing stages by even 5% to 10% would result in significant improvement in care and economic benefits. Noninvasive imaging could aid in both establishing the diagnosis of suspicious skin lesions and streamlining the surgical management of skin cancers by improving presurgical estimates of tumor sizes. Herein, we review the current state of imaging techniques in dermatology and their applications for diagnosis and tumor margin assessment of basal cell carcinoma prior to Mohs micrographic surgery.

Automatic Suppression Method for Water Surface Glints Using a Division of Focal Plane Visible Polarimeter.

To address the problem of water surface detection imaging equipment being susceptible to water surface glints, this study demonstrates a method called De-Glints for suppressing glints and obtaining clear underwater images using a division of focal plane (DoFP) polarimeter. Based on the principle of polarization imaging, the best polarization angle and the image corresponding to the minimal average gray level of each pixel are calculated. To evaluate the improvement in image quality, the index E was designed. The results of indoor and outdoor experiments show that the error of the angle calculation of this method is within 10%, and the minimum error is only 3%. The E index is positively improved and can be relatively improved by 8.00 under the interference of strong outdoor glints, and the method proposed in this paper shows a good adaptive ability to the dynamic scene.

Three Dimensional Shape Reconstruction via Polarization Imaging and Deep Learning.

Deep-learning-based polarization 3D imaging techniques, which train networks in a data-driven manner, are capable of estimating a target's surface normal distribution under passive lighting conditions. However, existing methods have limitations in restoring target texture details and accurately estimating surface normals. Information loss can occur in the fine-textured areas of the target during the reconstruction process, which can result in inaccurate normal estimation and reduce the overall reconstruction accuracy. The proposed method enables extraction of more comprehensive information, mitigates the loss of texture information during object reconstruction, enhances the accuracy of surface normal estimation, and facilitates more comprehensive and precise reconstruction of objects. The proposed networks optimize the polarization representation input by utilizing the Stokes-vector-based parameter, in addition to separated specular and diffuse reflection components. This approach reduces the impact of background noise, extracts more relevant polarization features of the target, and provides more accurate cues for restoration of surface normals. Experiments are performed using both the DeepSfP dataset and newly collected data. The results show that the proposed model can provide more accurate surface normal estimates. Compared to the UNet architecture-based method, the mean angular error is reduced by 19%, calculation time is reduced by 62%, and the model size is reduced by 11%.

Detection and Classification of Cotton Foreign Fibers Based on Polarization Imaging and Improved YOLOv5.

It is important to detect and classify foreign fibers in cotton, especially white and transparent foreign fibers, to produce subsequent yarn and textile quality. There are some problems in the actual cotton foreign fiber removing process, such as some foreign fibers missing inspection, low recognition accuracy of small foreign fibers, and low detection speed. A polarization imaging device of cotton foreign fiber was constructed based on the difference in optical properties and polarization characteristics between cotton fibers. An object detection and classification algorithm based on an improved YOLOv5 was proposed to achieve small foreign fiber recognition and classification. The methods were as follows: (1) The lightweight network Shufflenetv2 with the Hard-Swish activation function was used as the backbone feature extraction network to improve the detection speed and reduce the model volume. (2) The PANet network connection of YOLOv5 was modified to obtain a fine-grained feature map to improve the detection accuracy for small targets. (3) A CA attention module was added to the YOLOv5 network to increase the weight of the useful features while suppressing the weight of invalid features to improve the detection accuracy of foreign fiber targets. Moreover, we conducted ablation experiments on the improved strategy. The model volume, mAP@0.5, mAP@0.5:0.95, and FPS of the improved YOLOv5 were up to 0.75 MB, 96.9%, 59.9%, and 385 f/s, respectively, compared to YOLOv5, and the improved YOLOv5 increased by 1.03%, 7.13%, and 126.47%, respectively, which proves that the method can be applied to the vision system of an actual production line for cotton foreign fiber detection.

Polarization Super-Resolution Imaging Method Based on Deep Compressed Sensing.

The division of focal plane (DoFP) polarization imaging sensors, which can simultaneously acquire the target's two-dimensional spatial information and polarization information, improves the detection resolution and recognition capability by capturing the difference in polarization characteristics between the target and the background. In this paper, we propose a novel polarization imaging method based on deep compressed sensing (DCS) by adding digital micromirror devices (DMD) to an optical system and simulating the polarization transmission model of the optical system to reconstruct high-resolution images under low sampling rate conditions. By building a simulated dataset, training a polarization super-resolution imaging network, and showing excellent reconstructions on real shooting scenes, compared to current algorithms, our model has a higher peak signal-to-noise ratio (PSNR), which validates the feasibility of our approach.

Stress Detection of Conical Frustum Windows in Submersibles Based on Polarization Imaging.

Stress detection of the conical frustum window is a very important issue to ensure the safety of deep manned submersibles. In this paper, we propose a method based on polarization imaging to evaluate the stress accumulation and recovery in the conical frustum window. An experimental setup of Mueller matrix polarimetry is built, and the samples are made by referring to the typical conical frustum windows in submersibles. By pressurizing different pressures on the samples, we can find the changes of their Mueller matrix images and further derived polarization parameters. The results show that the polarization parameters can characterize the stress transfer process and the elastic-plastic transformation process of the window under different pressurization pressures. We also use a two-layered wave plate model to simulate the stress distribution in the window, which reveals different performances of the former and latter layers of the window under pressurization. Finally, we use a finite element model to simulate and understand some of the above experimental results. This proposed method is expected to provide new possibilities for monitoring the window stress and further ensure the safety of deep manned submersibles.

Cloud Detection Method Based on All-Sky Polarization Imaging.

Sky cloud detection has a significant application value in the meteorological field. The existing cloud detection methods mainly rely on the color difference between the sky background and the cloud layer in the sky image and are not reliable due to the variable and irregular characteristics of the cloud layer and different weather conditions. This paper proposes a cloud detection method based on all-sky polarization imaging. The core of the algorithm is the "normalized polarization degree difference index" (NPDDI). Instead of relying on the color difference information, this index identifies the difference between degree of polarization (DoPs) of the cloud sky and the clear sky radiation to achieve cloud recognition. The method is not only fast and straightforward in the algorithm, but also can detect the optical thickness of the cloud layer in a qualitative sense. The experimental results show a good cloud detection performance.

Comparison of High-Speed Polarization Imaging Methods for Biological Tissues.

We applied a polarization filter array and high-speed camera to the imaging of biological tissues during large, dynamic deformations at 7000 frames per second. The results are compared to previous measurements of similar specimens using a rotating polarizer imaging system. The polarization filter eliminates motion blur and temporal bias from the reconstructed collagen fiber alignment angle and retardation images. The polarization imaging configuration dose pose additional challenges due to the need for calibration of the polarization filter array for a given sample in the same lighting conditions as during the measurement.

Experimental Study on Bottom-Up Detection of Underwater Targets Based on Polarization Imaging.

Previous studies on the polarization imaging of underwater targets mainly focused on top-down detection; however, the capacities of bottom-up detection were poorly known. Based on in situ experiments, the capability of bottom-up detection of underwater targets using polarization imaging was investigated. First, to realize the objective of bottom-up polarization imaging, a SALSA polarization camera was integrated into our Underwater Polarization Imaging System (UPIS), which was integrated with an attitude sensor. At Qiandao Lake, where the water is relatively clear, experiments were conducted to examine the capacity of the UPIS to detect objects from the bottom up. Simultaneously, entropy, clarity, and contrast were adopted to compare the imaging performance with different radiation parameters. The results show that among all the used imaging parameters, the angle of polarization is the optimal parameter for bottom-up detection of underwater targets based on polarization imaging, which may result from the different diffused reflectance of the target surface to the linear polarization components of the Stokes vector.

Parallel Polarization Illumination with a Multifocal Axicon Metalens for Improved Polarization Imaging.

Polarization imaging is an important branch of the microscopy technique that can provide additional information and enhanced contrast. The illumination system of a polarization microscope enables many different polarizations but makes the setup bulky, complicated, and slow. Here, we design and fabricate an ultrathin planar axicon metalens that also enables parallel illumination with different polarizations. Our results reveal a diffraction-limited size and high degree of linear polarization. To verify our approach, we accurately map the polarization angle of an aluminum grating, which is used as a polarizer. Furthermore, we demonstrate that elliptical polarization can be generated without additional design. A single metalens has the same capabilities as a conventional illumination module containing a polarizer, compensator, and rotation-stage/optical modulator. In addition, our device has the potential to enable rapid super-resolution polarization imaging. The new method could be useful in many applications and areas, including, e.g., materials research and biomedicine.

Correlations in Joint Spectral and Polarization Imaging.

Recent imaging techniques enable the joint capture of spectral and polarization image data. In order to permit the design of computational imaging techniques and future processing of this information, it is interesting to describe the related image statistics. In particular, in this article, we present observations for different correlations between spectropolarimetric channels. The analysis is performed on several publicly available databases that are unified for joint processing. We perform global investigation and analysis on several specific clusters of materials or reflection types. We observe that polarization channels generally have more inter-channel correlation than the spectral channels.

Orientation Matters: Polarization Dependent IR Spectroscopy of Collagen from Intact Tendon Down to the Single Fibril Level.

Infrared (IR) spectroscopy has been used for decades to study collagen in mammalian tissues. While many changes in the spectral profiles appear under polarized IR light, the absorption bands are naturally broad because of tissue heterogeneity. A better understanding of the spectra of ordered collagen will aid in the evaluation of disorder in damaged collagen and in scar tissue. To that end, collagen spectra have been acquired with polarized far-field (FF) Fourier Transform Infrared (FTIR) imaging with a Focal Plane Array detector, with the relatively new method of FF optical photothermal IR (O-PTIR), and with nano-FTIR spectroscopy based on scattering-type scanning near-field optical microscopy (s-SNOM). The FF methods were applied to sections of intact tendon with fibers aligned parallel and perpendicular to the polarized light. The O-PTIR and nano-FTIR methods were applied to individual fibrils of 100-500 nm diameter, yielding the first confirmatory and complementary results on a biopolymer. We observed that the Amide I and II bands from the fibrils were narrower than those from the intact tendon, and that both relative intensities and band shapes were altered. These spectra represent reliable profiles for normal collagen type I fibrils of this dimension, under polarized IR light, and can serve as a benchmark for the study of collagenous tissues.

Design of Polarization Imaging Detection System for Lung Cancer Cells Based on Microfluidic Chip.

Lung cancer has become an important killer that endangers human health. In order to detect lung cancer cells at an early stage, prevent the proliferation of cancer cells, timely identify and treat cancer cells, a polarization imaging detection system for lung cancer cells based on microfluidic microarray is proposed. The system utilizes the different polarization characteristics of lung cancer cells to detect the polarization of lung cancer cells. Polarization imaging analyzes the pathological changes of biological tissues with imaging polarization degree and polarization difference images, so as to detect the differences between normal areas and pathological areas, and thus detect the differences between normal cells and cancer cells and carry out early treatment and prevention. Therefore, this system design has important research significance in medicine.

Survey of Demosaicking Methods for Polarization Filter Array Images.

Snapshot polarization imaging has gained interest in the last few decades. Recent research and technology achievements defined the polarization Filter Array (PFA). It is dedicated to division-of-focal plane polarimeters, which permits to analyze the direction of light electric field oscillation. Its filters form a mosaicked pattern, in which each pixel only senses a fraction of the total polarization states, so the other missing polarization states have to be interpolated. As for Color or Spectral Filter Arrays (CFA or SFA), several dedicated demosaicking methods exist in the PFA literature. Such methods are mainly based on spatial correlation disregarding inter-channel correlation. We show that polarization channels are strongly correlated in images. We therefore propose to extend some demosaicking methods from CFA/SFA to PFA, and compare them with those that are PFA-oriented. Objective and subjective analysis show that the pseudo panchromatic image difference method provides the best results and can be used as benchmark for PFA demosaicking.

Noninvasive assessment of cutaneous alterations in mice exposed to whole body gamma irradiation using optical imaging techniques.

We report the results of a study carried out to investigate the potential of optical techniques such as optical coherence tomography, Mueller matrix spectroscopy, and cross-polarization imaging for noninvasive monitoring of the ionizing radiation exposure-induced alterations in cutaneous tissue of mice. Radiation dose-dependent changes were observed in tissue microvasculature and tissue optical parameters like retardance and depolarization as early as 1 h post radiation exposure. Results suggest that these optical techniques may allow early detection of radiation dose-dependent alterations which could help in screening of population exposed to radiation.

Can invertebrates see the e-vector of polarization as a separate modality of light?

The visual world is rich in linearly polarized light stimuli, which are hidden from the human eye. But many invertebrate species make use of polarized light as a source of valuable visual information. However, exploiting light polarization does not necessarily imply that the electric (e)-vector orientation of polarized light can be perceived as a separate modality of light. In this Review, I address the question of whether invertebrates can detect specific e-vector orientations in a manner similar to that of humans perceiving spectral stimuli as specific hues. To analyze e-vector orientation, the signals of at least three polarization-sensitive sensors (analyzer channels) with different e-vector tuning axes must be compared. The object-based, imaging polarization vision systems of cephalopods and crustaceans, as well as the water-surface detectors of flying backswimmers, use just two analyzer channels. Although this excludes the perception of specific e-vector orientations, a two-channel system does provide a coarse, categoric analysis of polarized light stimuli, comparable to the limited color sense of dichromatic, 'color-blind' humans. The celestial compass of insects employs three or more analyzer channels. However, that compass is multimodal, i.e. e-vector information merges with directional information from other celestial cues, such as the solar azimuth and the spectral gradient in the sky, masking e-vector information. It seems that invertebrate organisms take no interest in the polarization details of visual stimuli, but polarization vision grants more practical benefits, such as improved object detection and visual communication for cephalopods and crustaceans, compass readings to traveling insects, or the alert 'water below!' to water-seeking bugs.

Polarization enhanced wide-field imaging for evaluating dermal changes caused by non-ablative fractional laser treatment.

BACKGROUND AND OBJECTIVE: Laser non-ablative fractional treatment (NAFT) is an important part of armamentarium of modern dermatology. Recently, such treatments have become available in at-home setting due to advent of self-application NAFT devices. Safety and clinical efficacy of NAFT are well established in multiple studies. Less information is available on morphological and functional changes in tissue occurring as a result of NAFT. Polarization-enhanced multispectral wide-field imaging device allows for in vivo real time visualization of dermal structures. The objective of this study is to use this imaging modality to monitor early effects of the home-use NAFT on collagen networks. MATERIALS AND METHODS: Eight subjects (skin types I-III) used a commercially available NAFT device (wavelength 1410 nm, energy per pulse up to 15 mJ) to treat peri-orbital wrinkles in standard recommended mode, that is daily, for a period of two weeks. In each session, subjects applied a pre-treatment gel to the peri-orbital areas and then used the device, delivering 8-10 applications to each side of the face without overlap. Subjects were asked to use the highest device setting. Cross-polarized 440 nm wide-field images were acquired from peri-orbital areas before and two weeks after the onset of the treatment regimen. Wide-field images were normalized and thresholded to a level of 40% brightness to emphasize collagen structure. Collagen content was quantitatively determined from thresholded collagen images. Improvement in collagen content at two weeks of daily treatments was assessed. RESULTS: Eight subjects (age 24-53 years) completed the study. Cross-polarized 440 nm wide-field images clearly delineated collagen networks. Quantitative assessment of collagen images revealed statistically significant (P < 0.05) improvement of collagen content at a time point of two weeks. Seven out of eight subjects showed varying degree of improvement. The increase of collagen content in responders ranged from 1-26%, with the mean improvement of 11%. Subjects in their early 40s showed the best improvement in comparison to younger and older age groups. CONCLUSIONS: Polarization-enhanced multispectral wide-field reflectance imaging method is a suitable technique for noninvasive in vivo assessment of dermal structures. Post-treatment images, taken three days after the last treatment session, demonstrate that non-ablative fractional treatment resulted in increased dermal collagen content as measured by the polarization-enhanced technique as early as two weeks post onset of the treatments. However, further studies with a larger number of subjects and longer treatment period are required to determine the optimal regimen and how long the results will last.

Polarization imaging and classification of Jurkat T and Ramos B cells using a flow cytometer.

Label-free and rapid classification of cells can have awide range of applications in biology. We report a robust method of polarization diffraction imaging flow cytometry (p-DIFC) for achieving this goal. Coherently scattered light signals are acquired from single cells excited by a polarized laser beam in the form of two cross-polarized diffraction images. Image texture and intensity parameters are extracted with a gray level co-occurrence matrix (GLCM) algorithm to obtain an optimized set of feature parameters as the morphological "fingerprints" for automated cell classification. We selected the Jurkat T cells and Ramos B cells to test the p-DIFC method's capacity for cell classification. After detailed statistical analysis, we found that the optimized feature vectors yield accuracies of classification between the Jurkat and Ramos ranging from 97.8% to 100% among different cell data sets. Confocal imaging and three-dimensional reconstruction were applied to gain insights on the ability of p-DIFC method for classifying the two cell lines of highly similar morphology. Based on these results we conclude that the p-DIFC method has the capacity to discriminate cells of high similarity in their morphology with "fingerprints" features extracted from the diffraction images, which may be attributed to subtle but statistically significant differences in the nucleus-to-cell volume ratio in the case of Jurkat and Ramos cells.