Polarimetric Images Research Articles

Quasi-simultaneous photometric, polarimetric, and spectral observations of distant comet C/2014 B1 (Schwartz)

Context. We analyze the results of our comprehensive observations of the high-perihelion comet C/2014 B1 (Schwartz) with stable disk-shaped coma and jets in order to study its nature. Aims. The main objective of our study is to obtain new observational results for a unique disk-like comet C/2014 B1 (Schwartz) with a perihelion distance of 9.56 au. Methods. Quasi-simultaneous long-slit spectra, as well as photometric and polarimetric images with g-sdss and r-sdss filters, were acquired with the 6 m telescope of the Special Astrophysical Observatory on 2017 January 23. The BVR-band photometry of the comet was also performed at the 2m telescope of the Peak Terskol Observatory on 2017 January 31. We modeled the dynamics of the jets and the behavior of the color and polarization in the coma considering the dust as aggregated large particles. Results. We did not reveal any emissions in the spectra. The positions of two jets oriented along the position angles of 179° and 350° and the disk-like shape of the coma have remained unchanged for more than 4 yr. The most realistic model able to explain jets of such stable orientation includes the existence of two active sources located near the north and south poles of the rotating nucleus whose diameter was determined to be between 7.6 and 12.2 km depending on the albedo, of namely between 0.1 and 0.04, respectively. The high activity of the comet is characterized by the high dust production Afρ which varied from 4440 to 3357 cm between 2017 January 23 and 31. A significant difference between the radial surface brightness profiles of the jets and the ambient (undisturbed by the jets) coma is found. The color of the jet structures is much redder than that of the ambient coma, and the nucleus has a very red color, V − R=0.93m±0.19m. There are spatial variations of the color and polarization over the coma and jets. Conclusions. The observed trends in color and polarization, as well as the brightness profiles, can be explained by the fragmentation of aggregated particles formed by CO2/H2O ices, silicates, and organics, which are of ~1 mm in radius near the nucleus and ~10 μm in radius at the periphery of the coma.

Fundamental Study on Grasping Growth State of Paddy Rice Using Quad-Polarimetric SAR Data

In this brief paper, we examine polarimetric scattering characteristics for understanding seasonal change of paddy rice growth by using quad-polarimetric synthetic aperture radar (SAR) data in the X-band. Here we carry out polarimetric scattering measurement for a simplified paddy rice model in an anechoic chamber at X-band frequency to acquire the the quad polarimetric SAR data from the model. The measurements are performed several times for each growth stage of the paddy rice corresponding to seasonal change. The model-based scattering power decomposition is used for the examination of polarimetric features of the paddy rice model. It is found from the result of the polarimetric SAR image analysis for the measurement data that the growth state of the paddy rice in each stage can be understood by considering the ratio of the decomposition powers, when the planting direction of the paddy rice is not only normal but also oblique to radar direction. We can also see that orientation angle compensation (OAC) is useful for improving the accuracy of the growth stage observation in late vegetative stage for oblique planting case.

Depolarization Measurement through a Single-Mode Fiber-Based Endoscope for Full Mueller Endoscopic Polarimetric Imaging

Coupled to endoscopic techniques, Mueller polarimetry has been proven to be promising for early detection of certain diseases which affect biological tissues of inner organs. However, the depolarization power which is one of the most informative polarimetric characteristics cannot be directly measured through a fiber endoscope. For evaluating this quantity, we propose a method based on the Lu–Chipman decomposition of the averaged sum of the Mueller matrices of neighboring pixels. The principle is well supported by numerical simulations. Depolarization powers of Spectralon and of different areas of a biological sample are also successfully evaluated.

The high-albedo, low polarization disk around HD 114082 that harbors a Jupiter-sized transiting planet

Aims. We present new optical and near-infrared images of the debris disk around the F-type star HD 114082 in the Scorpius-Centaurus OB association. We obtained direct imaging observations and analyzed the TESS photometric time series data of this target with the goal of searching for planetary companions to HD 114082 and characterizing the morphology of the debris disk and the scattering properties of dust particles. Methods. HD 114082 was observed with the VLT/SPHERE instrument in different modes – the IRDIS camera in the K band (2.0–2.3 μm) together with the IFS in the Y, J, and H bands (0.95–1.66 μm) using the angular differential imaging technique as well as IRDIS in the H band (1.5–1.8 μm) and ZIMPOL in the I_PRIME band (0.71–0.87 μm) using the polarimetric differential imaging technique. To constrain the basic geometrical parameters of the disk and the scattering properties of dust grains, scattered light images were fitted with a 3D model for single scattering in an optically thin dust disk using a Markov chain Monte Carlo approach. We performed aperture photometry to derive the scattering and polarized phase functions, the polarization fraction, and the spectral scattering albedo for the dust particles in the disk. This method was also used to obtain the reflectance spectrum of the disk and, in turn, to retrieve the disk color and study the dust reflectivity in comparison to the debris disk HD 117214. We also performed the modeling of the HD 114082 light curve measured by TESS using models for planet transit and stellar activity to put constraints on the radius of the detected planet and its orbit. Last, we searched for additional planets in the system by combining archival radial velocity data, astrometry, and direct imaging. Results. The debris disk HD 114082 appears as an axisymmetric debris belt with a radius of ~0.37″ (35 au), an inclination of ~83°, and a wide inner cavity. Dust particles in HD 114082 have a maximum polarization fraction of ~17% and a higher reflectivity when compared to the debris disk HD 117214. This high reflectivity results in a spectral scattering albedo of ~0.65 for the HD 114082 disk at near-infrared wavelengths. The disk reflectance spectrum exhibits a red color at the position of the planetesimal belt and shows no obvious features, whereas that of HD 117214 might indicate the presence of CO2 ice. The analysis of TESS photometric data reveals a transiting planetary companion to HD 114082 with a radius of ~1 RJup on an orbit with a semimajor axis of 0.7 ± 0.4 au. No additional planet was detected in the system when we combined the SPHERE images with constraints from astrometry and radial velocity. We reach deep sensitivity limits down to ~5 MJup at 50 au and ~10 MJup at 30 au from the central star.

Polarimetric imaging of back-scattered terahertz speckle fields using a portable scanner.

Speckle patterns observed in coherent optical imaging reflect important characteristic information of the scattering object. To capture speckle patterns, angular resolved or oblique illumination geometries are usually employed in combination with Rayleigh statistical models. We present a portable and handheld 2-channel polarization-sensitive imaging instrument to directly resolve terahertz (THz) speckle fields in a collocated telecentric back-scattering geometry. The polarization state of the THz light is measured using two orthogonal photoconductive antennas and can be presented in the form of the Stokes vectors of the THz beam upon interaction with the sample. We report on the validation of the method in surface scattering from gold-coated sandpapers, demonstrating a strong dependence of the polarization state on the surface roughness and the frequency of the broadband THz illumination. We also demonstrate non-Rayleigh first-order and second-order statistical parameters, such as degree of polarization uniformity (DOPU) and phase difference, for quantifying the randomness of polarization. This technique provides a fast method for broadband THz polarimetric measurement in the field and has the potential for detecting light depolarization in applications ranging from biomedical imaging to non-destructive testing.

Polarimetric Imaging via Deep Learning: A Review

Polarization can provide information largely uncorrelated with the spectrum and intensity. Therefore, polarimetric imaging (PI) techniques have significant advantages in many fields, e.g., ocean observation, remote sensing (RS), biomedical diagnosis, and autonomous vehicles. Recently, with the increasing amount of data and the rapid development of physical models, deep learning (DL) and its related technique have become an irreplaceable solution for solving various tasks and breaking the limitations of traditional methods. PI and DL have been combined successfully to provide brand-new solutions to many practical applications. This review briefly introduces PI and DL’s most relevant concepts and models. It then shows how DL has been applied for PI tasks, including image restoration, object detection, image fusion, scene classification, and resolution improvement. The review covers the state-of-the-art works combining PI with DL algorithms and recommends some potential future research directions. We hope that the present work will be helpful for researchers in the fields of both optical imaging and RS, and that it will stimulate more ideas in this exciting research field.

Polarimetric imaging for the detection of synthetic models of SARS-CoV-2: A proof of concept

ObjectiveTo conduct a proof-of-concept study of the detection of two synthetic models of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using polarimetric imaging. ApproachTwo SARS-CoV-2 models were prepared as engineered lentiviruses pseudotyped with the G protein of the vesicular stomatitis virus, and with the characteristic Spike protein of SARS-CoV-2. Samples were prepared in two biofluids (saline solution and artificial saliva), in four concentrations, and deposited as 5-µL droplets on a supporting plate. The angles of maximal degree of linear polarization (DLP) of light diffusely scattered from dry residues were determined using Mueller polarimetry from87 samples at 405 nm and 514 nm. A polarimetric camera was used for imaging several samples under 380–420 nm illumination at angles similar to those of maximal DLP. Per-pixel image analysis included quantification and combination of polarization feature descriptors in 475 samples. Main resultsThe angles (from sample surface) of maximal DLP were 3° for 405 nm and 6° for 514 nm. Similar viral particles that differed only in the characteristic spike protein of the SARS-CoV-2, their corresponding negative controls, fluids, and the sample holder were discerned at 10-degree and 15-degree configurations. SignificancePolarimetric imaging in the visible spectrum may help improve fast, non-contact detection and identification of viral particles, and/or other microbes such as tuberculosis, in multiple dry fluid samples simultaneously, particularly when combined with other imaging modalities. Further analysis including realistic concentrations of real SARS-CoV-2 viral particles in relevant human fluids is required. Polarimetric imaging under visible light may contribute to a fast, cost-effective screening of SARS-CoV-2 and other pathogens when combined with other imaging modalities.

Fast image visibility enhancement based on active polarization and color constancy for operation in turbid water.

Vehicles operating in a water medium sometimes encounter harsh conditions with high turbidity and low scene illumination, making it challenging to obtain reliable target information through optical devices. Although many post-processing solutions were proposed, they are not applicable to continuous vehicle operations. Inspired by the advanced polarimetric hardware technology, a joint fast algorithm was developed in this study to address the above problems. Backscatter attenuation and direct signal attenuation were solved separately by utilizing the revised underwater polarimetric image formation model. A fast local adaptive Wiener filtering method was used to improve the backscatter estimation by reducing the additive noise. Further, the image was recovered using the fast local space average color method. By using a low-pass filter guided by the color constancy theory, the problems of nonuniform illumination caused by artificial light and direct signal attenuation were both addressed. The results of testing on images from laboratory experiments showed improved visibility and realistic chromatic rendition.

PolSAR Image Building Extraction with G0 Statistical Texture Using Convolutional Neural Network and Superpixel

Polarimetric synthetic aperture radar (PolSAR) has unique advantages in building extraction due to its sensitivity to building structures and all-time/all-weather imaging capabilities. However, the structure of buildings is complex, and buildings are easily confused with other objects in polarimetric SAR images. The speckle noise of SAR images will affect the accuracy of building extraction. This paper proposes a novel building extraction approach from PolSAR images with statistical texture and polarization features by using a convolutional neural network and superpixel. A feature space that is sensitive to building, including G0 statistical texture and PualiRGB features, is constructed and used as CNN input. Considering that the building boundary of the CNN classification result is inaccurate due to speckle noise, the simple linear iterative cluster (SLIC) superpixel is utilized to constrain the building extraction result. Finally, the effectiveness of the proposed method has been verified by experimenting with PolSAR images from three different sensors, including ESAR, GF-3, and RADARSAT-2. Experiment results show that compared with the other five PolSAR building extraction methods including threshold, SVM, RVCNN, and PFDCNN, our method without superpixel constraint, the F1-score of this method is the highest, reaching 84.22%, 91.24%, and 87.49%, respectively. The false alarm rate of this method is at least 10% lower and the F1 index is at least 6% higher when the building extraction accuracy is comparable. Further, the discussion and method parameter analysis results show that increasing the use of G0 statistical texture parameters can improve building extraction accuracy and reduce false alarms, and the introduction of superpixel constraints can further reduce false alarms.

Comparative assessment of polarimetric features estimation in fully polarimetric 3D-ISAR imaging system

Comparative assessment of polarimetric features estimation in fully polarimetric 3D-ISAR imaging system

Optical detection of ensonified capillary-gravity waves using polarimetric imaging

The optical detection of surface capillary-gravity waves induced by underwater sound has many potential applications that range from the detection of sound-generating underwater objects to airborne bathymetric surveys. While multiple lab-based efforts have measured acoustically generated surface capillary-gravity waves, we report on a recent field-based measurement using polarimetric imaging. A controlled acoustic source was placed 10 m below a lake surface and emitted sound in the 500 Hz to 10000Hz frequency range. The lake surface was imaged using a polarimetric camera mounted 7 m above the lake surface. Measurable short-lived surface capillary-gravity waves (∼3 mm wavelength) were observed in the polarimetric camera images during ensonification of the lake surface. Changes were observed in both the omnidirectional and directional wave spectra. In the omni-directional wavenumber spectrum, enhanced capillary wave activity at high wavenumbers was observed for acoustic source frequencies in the 2–5 kHz range. Additionally, ensonification was observed to result in the amplitude and wavenumber modulation (enhancement/diminution) of existing wind-generated surface gravity-capillary waves. In the directional spectra, while ambient gravity-capillary waves showed a spreading function with stronger downwind versus upwind propagation, the acoustically generated gravity-capillary waves showed minimal impact on the directionality of the wave spectra.

General Five-Component Scattering Power Decomposition with Unitary Transformation (G5U) of Coherency Matrix

The polarimetric synthetic aperture radar (PolSAR) provides us with a two-by-two scattering matrix data set. The ensemble averaged coherency matrix in an imaging window derived using a scattering matrix has all non-zero elements in its three-by-three matrix. It is a full 3 × 3 matrix that bears nine real-valued and independent polarimetric parameters inside. In the proposed decomposition method, G5U, we preprocess observed coherency matrix [T] by using two consecutive unitary transformations to become an ideal form for five-component decomposition. The transformation reduces nine parameters to seven, which is the best fit for five-component scattering model expansion. We can retrieve five powers corresponding to surface scattering, double bounce scattering, volume scattering, oriented dipole scattering, and compound dipole scattering, directly. These powers can be calculated easily and used to display superb polarimetric RBG images as never before, and are further applicable for polarimetric calibration, classification, validation, etc.

Jones tomographic diffractive microscopy with a polarized array sensor.

Tomographic diffractive microscopy (TDM) based on scalar light-field approximation is widely implemented. Samples exhibiting anisotropic structures, however, necessitate accounting for the vectorial nature of light, leading to 3-D quantitative polarimetric imaging. In this work, we have developed a high-numerical aperture (at both illumination and detection) Jones TDM system, with detection multiplexing via a polarized array sensor (PAS), for imaging optically birefringent samples at high resolution. The method is first studied through image simulations. To validate our setup, an experiment using a sample containing both birefringent and non-birefringent objects is performed. Araneus diadematus spider silk fiber and Pinna nobilis oyster shell crystals are finally studied, allowing us to assess both birefringence and fast-axis orientation maps.

Evaluation and characterization of imaging polarimetry through metasurface polarization gratings.

Metasurfaces are a new class of diffractive optical elements with subwavelength elements whose behavior can be lithographically tailored. By leveraging form birefringence, metasurfaces can serve as multifunctional freespace polarization optics. Metasurface gratings are novel, to the best of our knowledge, polarimetric components that integrate multiple polarization analyzers into a single optical element enabling the realization of compact imaging polarimeters. The promise of metasurfaces as a new polarization building block is contingent on the calibration of metagrating-based optical systems. A prototype metasurface full Stokes imaging polarimeter is compared to a benchtop reference instrument using an established linear Stokes test for 670, 532, and 460 nm gratings. We propose a complementary full Stokes accuracy test and demonstrate it using the 532 nm grating. This work presents methods and practical considerations involved in producing accurate polarization data from a metasurface-based Stokes imaging polarimeter and informs their use in polarimetric systems more generally.

Sparse representation-based demosaicking method for joint chromatic and polarimetric imagery

Division of focal plane (DoFP) polarization camera has become mainstream among various polarimetric imaging systems whose sensor is equipped with Bayer filter and directional polarization filter, so joint chromatic and polarimetric image demosaicking is essential. However, since 15 or 14 pixels are missed out of 16 pixels in color polarization mosaic images, it’s challenging to adopt a method to reconstruct full-resolution images well. In this paper, we propose a demosaicking model based on sparse coding. The model introduces RGB-polarization channels correlation, adaptive sub-dictionaries and non-local self-similarity restrictions, and combines them into an optimal problem to solve. The experimental results, including reconstructing full-resolution synthetic images and camera captured real scenes, demonstrate that our proposed method outperforms the current state-of-the-art method in terms of quantitative measures and visual quality.

Using Machine Learning to link black hole accretion flows with spatially resolved polarimetric observables

ABSTRACT We introduce a new library of 535 194 model images of the supermassive black holes and Event Horizon Telescope (EHT) targets Sgr A* and M87*, computed by performing general relativistic radiative transfer calculations on general relativistic magnetohydrodynamics simulations. Then to infer underlying black hole and accretion flow parameters (spin, inclination, ion-to-electron temperature ratio, and magnetic field polarity), we train a random forest machine learning model on various hand-picked polarimetric observables computed from each image. Our random forest is capable of making meaningful predictions of spin, inclination, and the ion-to-electron temperature ratio, but has more difficulty inferring magnetic field polarity. To disentangle how physical parameters are encoded in different observables, we apply two different metrics to rank the importance of each observable at inferring each physical parameter. Details of the spatially resolved linear polarization morphology stand out as important discriminators between models. Bearing in mind the theoretical limitations and incompleteness of our image library, for the real M87* data, our machinery favours high-spin retrograde models with large ion-to-electron temperature ratios. Due to the time-variable nature of these targets, repeated polarimetric imaging will further improve model inference as the EHT and next-generation (EHT) continue to develop and monitor their targets.

Efficient machine learning method for spatio-temporal water surface waves reconstruction from polarimetric images

Accurate and cost-effective sea state measurements, in terms of spatio-temporal distribution of water surface elevation (water waves), is of great interest for scientific research and various engineering, industrial, and recreational applications. To this end, numerous measurement techniques have been developed over the years. None of these techniques, however, are universally applicable across various ocean and laboratory conditions and none provide near-real-time data. We utilized the latest advances in polarimetric imaging to develop a new remote sensing method based on machine learning methodology and polarimetric reflection measurements for inferring surface waves elevation and slope. The method utilizes a newly available, inexpensive polarimetric camera providing images of the water surface in a high spatio-temporal resolution at several linear polarization angles. Algorithms based on artificial neural networks (s) are then trained to obtain high-resolution reconstructions of the water surface slope state from those images. The s are trained on laboratory-collected supervised datasets of prescribed mechanically generated monochromatic wave trains and tested on a stochastic wave field of JONSWAP spectral shape. The proposed method, based on inferring the surface slope from polarimetric images, provides a dense estimate of the water surface. The results of this study pave the way for the development of accurate and cost-effective near-real-time remote sensing tools for both laboratory and open sea wave measurements.

Automatic Ship Detection Using PolSAR Imagery and the Double Scatterer Model

In ship detection by means of Polarimetric SAR imagery, a very promising feature is the characterization of the pixels of the ship based on the elementary scattering mechanisms that can be extracted using different decomposition algorithms. Elementary scattering mechanisms provide information regarding the physical, electrical and geometrical properties of the scatterers in each Polarimetric SAR pixel. In this work, the newly established algorithm of the Double Scatterer Model is applied to interpret each pixel of the Polarimetric SAR image with the contributions of two elementary scattering mechanisms, namely, primary and secondary. The main idea is to construct a binary image while preserving the rich information content in order to proceed in simple and fast image processing for target detection. The present algorithm is applied to datasets with different inherent characteristics acquired by Radarsat-2 and ALOS-PALSAR. The results presented by this new perspective on ship monitoring are remarkable.

Innovative Solutions Based on the EM-Algorithm for Covariance Structure Detection and Classification in Polarimetric SAR Images

This article addresses the challenge of identifying the polarimetric covariance matrix (PCM) structures associated with a polarimetric synthetic aperture radar (SAR) image. Interestingly, such information can be used, for instance, to improve the scene interpretation or to enhance the performance of (possibly PCM-based) segmentation algorithms as well as other kinds of methods. To this end, a general framework to solve a multiple hypothesis test is introduced with the aim to detect and classify contextual spatial variations in polarimetric SAR images. Specifically, under the null hypothesis, only one unknown structure is assumed for data belonging to a two-dimensional spatial sliding window, whereas under each alternative hypothesis, data are partitioned into subsets sharing different PCM structures. The problem of partition estimation is solved by resorting to hidden random variables representative of covariance structure classes and the expectation–maximization algorithm. The effectiveness of the proposed detection strategies is demonstrated on both simulated and real polarimetric SAR data also in comparison with existing classification algorithms.

Active Polarization Imaging for Cross-Linear Image Histogram Equalization and Noise Suppression in Highly Turbid Water

The absorption and scattering of impurity particles in turbid water cause the target signal light to be attenuated and to produce backscattered light, resulting in the reduced quality of underwater polarimetric imaging. As water turbidity increases, the effect of backscattered light becomes greater, making polarization imaging in highly turbid water a challenge. Theory and experiment show that the increase in the intensity of backscattered light leads to high noise gain in the underwater active polarization imaging model. In order to enhance image contrast and suppress noise gain in highly turbid water, we propose an underwater imaging enhancement method that appropriately combines the non-physical and physical models. The method uses contrast limited adaptive histogram equalization (CLAHE) for a certain number of cross-linear images (Imin) before calculating their polarization enhancement images, and it constructs joint filtering (multi-frame averaging and bilateral filtering) to suppress the high noise gain introduced by the imaging model and CLAHE. The experimental results in highly turbid water validate the rationality and feasibility of the proposed method, and the comparative processing results (52.7~98.6 NTU) outperform those of the conventional non-physical and physical model methods. The method maintains the complexity of the system and facilitates the application of conventional polarimetric imaging in harsher underwater environments.