Polarimetric Imagery Research Articles

Material Classification of an Unknown Object Using Turbulence-Degraded Polarimetric Imagery

In this paper, a material-classification technique using polarimetric imagery degraded by atmospheric turbulence is presented. The classification technique described here determines whether an object is composed of dielectric or metallic materials. The technique implements a modified version of the LeMaster and Cain polarimetric maximum-likelihood blind-deconvolution algorithm in order to remove atmospheric distortion and correctly classify the unknown object. The dielectric/metal classification decision is based on degree-of-linear-polarization (DOLP) maximum-likelihood estimates provided by two novel DOLP priors (one being representative of dielectric materials and the other being representative of metallic materials) developed in this paper. The DOLP estimate, which maximizes the log-likelihood function, determines the image pixel's classification. Included in this paper is the review and modification of the LeMaster and Cain deconvolution algorithm. Also provided is the development of the novel DOLP priors, including their mathematical forms and the physical insight underlying their formulation. Lastly, the experimental results of two dielectric and metallic samples are provided to validate the proposed classification technique.

Determining the complex index of refraction of an unknown object using turbulence-degraded polarimetric imagery

A novel index-of-refraction material-characterization technique using passive polarimetric imagery degraded by atmospheric turbulence is presented. The method uses a variant of the LeMaster and Cain (J. Opt. Soc. Am. A 25(9), 2170-2176 (2008)) blind-deconvolution algorithm to recover the true object (i.e., the first Stokes parameter), the degree of linear polarization, and the polarimetric-image point spread functions. Nonlinear least squares is then used to find the value of the complex index of refraction that best fits the theoretical degree of linear polarization, derived using a polarimetric bidirectional reflectance distribution function, to the turbulence-corrected degree of linear polarization. To verify the proposed material-characterization technique, experimental results of two painted metal samples are provided and analyzed. C

Enhanced material classification using turbulence-degraded polarimetric imagery

An enhanced material-classification algorithm using turbulence-degraded polarimetric imagery is presented. The proposed technique improves upon an existing dielectric/metal material-classification algorithm by providing a more detailed object classification. This is accomplished by redesigning the degree-of-linear-polarization priors in the blind-deconvolution algorithm to include two subclasses of metals--an aluminum group classification (includes aluminum, copper, gold, and silver) and an iron group classification (includes iron, titanium, nickel, and chromium). This new classification provides functional information about the object that is not provided by existing dielectric/metal material classifiers. A discussion of the design of these new degree-of-linear-polarization priors is provided. Experimental results of two painted metal samples are also provided to verify the algorithm's accuracy.

Imaging polarimetry in the LWIR with microgrid polarimeters

Microgrid polarimeters have emerged over the past decade as a viable tool for performing real-time, highly accurate polarimetric imagery. A microgrid polarimeter operates by integrating a focal plane array (FPA) with an array of micropolarizing optics. Mircrogrids have the advantage of being relatively compact, rugged, and inherently spatiotemporally aligned. However, they have the single disadvantage that the various polarization measurements that go into estimating the Stokes parameters at a particular pixel are actually coming from separate locations in the field. Hence, a microgrid polarimeter performs best where there is no image information, obviating the need for an imaging polarimeter! Recently we have been working with a LWIR microgrid polarimeter at the College of Optical Sciences. Our instrument is a DRS Sensors & Targeting Systems 640 x 480 HgCdTe FPA with linear polarizers at 0°, 45°, 90°, and 135° [1]. In this paper we will review our recent results that derive methods for artifact-free reconstruction of band limited imagery.

Calibration of Polarimetric PALSAR Imagery Affected by Faraday Rotation Using Polarization Orientation

For spaceborne polarimetric synthetic aperture radar (SAR), it is important to ensure the removal of both polarimetric system distortion and the effect of Faraday rotation. This paper proposes a new calibration method to derive the system distortion using polarization orientation (PO) induced in built-up areas and applies to Phased-Array-Type L-Band SAR (PALSAR) calibration. Faraday rotation is corrected by the circular-polarization-based method from the distortion matrix (DM)-calibrated data. The derived DMs do not coincide with those by the Japan Aerospace Exploration Agency (JAXA), but our calibration results compare well to JAXA's results in PO angles and calibrator's responses. The two results satisfy polarimetric calibration requirements, and the cross-polarized isolation improves by more than 5 dB after Faraday rotation correction following DM calibration-even in the case of small Faraday rotation (-2deg to -0.5deg). The proposed method is robust to noise and is useful when using an area of mixed polarimetric response for calibration. This method is also applicable to a large crosstalk system and the case of large Faraday rotation.

Object separation by polarimetric and spectral imagery fusion

When light is reflected from object surface, its spectral characteristics will be affected by the surface’s elemental composition, and its polarimetric characteristics will be governed by the surface’s roughness and conductance. Polarimetric and multispectral imaging can provide complementary discriminative information in applications such as object separation. However, few methods have been proposed to fuse the information provided by polarimetric and multispectral imagery for better object separation results. Considering that the metal and dielectric materials, and the manmade objects and natural background have different polarimetric and multispectral features, in this paper we propose a simple yet powerful method for object separation by using the polarimetric and spectral characteristics of specular and diffuse reflected light. A polarimetric imagery fusion algorithm is first proposed based on the degree of linear polarization modulation to distinguish different objects. Then the spectral and polarimetric information, which can be extracted from the specular and diffuse reflected light, is fused by using the HSI color space mapping for more robust object separation. Experiments on real outdoor and indoor images are performed to evaluate the efficiency of the proposed scheme.

Multichannel blind deconvolution of polarimetric imagery

A maximum likelihood blind deconvolution algorithm is derived for incoherent polarimetric imagery using expectation maximization. In this approach, the unpolarized and fully polarized components of the scene are estimated along with the corresponding angles of polarization and channel point spread functions. The scene state of linear polarization is determined unambiguously using this parameterization. Results are demonstrated using laboratory data.

Fundamental estimation bounds for polarimetric imagery

Precise channel-to-channel registration is a prerequisite for effective exploitation of passive polarimetric imagery. In this paper, the Cramer-Rao bound is employed to determine the limits of registration precision in the presence of scene polarization diversity, channel noise, and random translational registration errors between channels. The effects of misregistration on Stokes image estimation are also explored in depth. The derived bound is then used to determine when joint estimation is preferable to externally provided registration correction. Finally, case studies are presented for polarization insensitive imagery (a special case) and linear polarization imaging systems with three and four channels. An optimum polarization channel arrangement is also proposed in the context of the bound.

Classifying Multifrequency Fully Polarimetric Imagery With Multiple Sources of Statistical Evidence and Contextual Information

This paper presents the use of a new distribution for fully polarimetric image classification. Several classification strategies are compared in order to assess the importance of a careful statistical modeling of the data and the complementary nature of the information provided by different frequencies. Spatial context, which is relevant in order to obtain good results with noisy data, is described by means of the multiclass Potts model, and an iterated conditional modes classification algorithm that employs pseudolikelihood is proposed. The data are described using multivariate Gaussian laws and fully multilook polarimetric distributions arising from the multiplicative model. L-band, C-band, and both bands are used to assess the influence of dimensionality on the classification. Contextual and pointwise maximum-likelihood classifications are compared using real data. Results show that both context and number of frequencies contribute for better classification products, and that, a careful statistical description of the data leads to improved results.

Parametric estimation of the square degree of polarization from two intensity images degraded by fully developed speckle noise

Active polarimetric imagery systems allow one to reveal polarimetric characteristics of the scene. Among them, the degree of polarization allows one to have information about the polarizing nature of an imaged object. Its estimation is standardly done from four images of the scene. Reducing this number of images can be of great interest for industrial applications, allowing in particular reduction of cost in terms of money and acquisition time. We propose a parametric method to estimate the square degree of polarization from only two measurements when coherent illumination is considered and when the images are corrupted with fully developed speckle, and we characterize the performances of the estimation.

The Study of Method for Feature Extraction Based on Angle of Polarization Parameter Image

Multispectral polarimetric imagery can provide several parameters of the man-made targets, including spectrum, intensity, state of polarization, and shapes. Among these, the state of polarization is additional useful information. It will help to improve the capabilities of the target detection and recognition. Recently, an experimental multiband polarized CCD camera has been built in our laboratory. It can obtain the polarimetric imaging information at four bands subsequently. Here, We use one kind of man-made target as an experimental sample. Many digital polarization imaging data were acquired in the field and the laboratory. Thereby the Stokes parameters I, Q and U were calculated according to the measured radiance images of three polarization directions at 0o, 60o and 120o relative orientation of the transmission optic axis of the linear polarizer. At last, the angle of polarization (AOP) image and intensity image were derived from Stokes parameters, respectively. These images were only analyzed at 443 nm waveband. The median filtering and single threshold method were adopted in angle of polarization image processing. Moreover, the vector images of the target were obtained. The result indicates that the properties of the man-made target and the background were characterized clearly by using the AOP parameter. The smooth surface of man-made target shows the coincident feature in AOP image. On the contrary, the surface of grass is unorderly. Indeed, it is the very function of the AOP image, which we want to illustrate. Hence, it shows that the AOP image can describe the different of surface orientations. Also, it may enhance the contrast between the man-made target and grass background. In a word, this new method based on the angle of polarization parameter can be used to discriminate the target from the background when we interpret the image of the polarized remote sensing.

Remote sensing using passive infrared Stokes parameters

We address the problem of detecting vehicle targets on the ground by means of an autonomous polarimetric sensor on board a high-altitude air- or spaceborne platform. We studied a sensor system that incorporates a micropolarizer array, a microscanner, and digital signal processors that host algorithms for detecting small targets. These algorithms use statistical techniques to fuse a target's Stokes-vector infrared signature measurements. Fusion is achieved by constructing the joint statistical measures for the target's polarization states. Those states are expressed in terms of the intensity, the percentage of linear polarization, and the angle of the polarization plane. The performance of the sensor system on synthetic polarimetric infrared imagery was evaluated. Relatively good detection and low false-alarm probabilities were achieved even when the number of pixels on targets is as small as four. This is the first report of the development and evaluation of automatic detection in polarimetric imagery containing targets subtending only a small number of pixels.

Detection of crashed aircraft in polarimetric imagery

This manuscript presents studies examining the use of C-band polarimetric Synthetic Aperture Radar (SAR) systems for the detection of crashed aircraft. The ultimate aim is to assist Search and Rescue in Canada in the location of such targets. Detection methodologies based on the Polarimetric Whitening Filter, Cameron Decomposition, and measures of even bounce contributions to the backscatter have been examined. Tests were performed using imagery of serviceable and crashed aircraft and crashed aircraft parts. Although individual methods make it possible to detect the crashed aircraft, best results for target detection with decreased numbers of false alarms occur when these methods are used in combination.

Applying polarimetric radar imagery for mapping the productivity of wheat crops

Airborne, fully polarimetric C-band radar imagery was acquired over an agricultural test site located in southern Ontario (Canada) on 30 June 1999. Approximately 2 weeks after this image acquisition, yield-monitor data were collected over two wheat fields. Zones of higher productivity had higher radar backscatter, for linear (HH, VV, HV) and circular (RR, LR) polarizations. Zones of productivity were classified using backscatter from the linear polarizations, and these classified maps agreed well with the maps generated by the yield monitors. The linear cross-polarization (HV) provided the greatest contrast between zones of high and low productivity, although the height of the cross-polarization pedestal also varied between these two classes. No significant differences were observed between high- and low-producing zones using either the copolarization pedestal height or the copolarization phase difference. This study demonstrated that polarimetric radar parameters such as the linear and circular polarizations and the cross-polarization pedestal height are sensitive to differences in wheat productivity.

Faraday rotation effects on l-band spaceborne sar data

Several proposed near-future spaceborne radar missions, such as the Advanced Land Observing Satellite (ALOS) and TerraSAR, will include an L-band instrument. At such low frequencies, the Faraday rotation in the ionosphere, which rotates the polarization plane of the radar signal, becomes an important consideration in instrument design. In this paper, both simple analytic approximations and numerical models are used to derive likely values of Faraday rotation and determine their impact on polarimetric imagery and derived products. One-way rotations exceeding 5/spl deg/ are likely to significantly reduce the accuracy of geophysical parameter recovery, such as forest biomass. On average, Faraday rotation can be neglected at solar minimum, but correction methods are needed at other times of the solar cycle and under disturbed conditions. Methods for implementing such corrections based on estimates of the Faraday rotation and prerotation of the transmitted signal are described.

Optimum detection and segmentation of oil-slicks using polarimetric SAR data

The paper is concerned with techniques for optimising the detection and definition of slick boundaries on the sea surface using polarimetric imagery. In principle, the full polarimetric return should provide more information than is available in a single polarisation. The authors compare the performance of a set of different polarisation measures applied to the detection of slicks. Annealed segmentation of these measures is then employed to detect and define their boundaries. Theoretical predictions are derived for the probability of detection using conventional polarisation measures, including the intensity in a single polarisation and the maximum eigenvalue and span measures for more than one polarisation channel. The authors also propose two implementations of a maximum likelihood polarisation discriminant and demonstrate that these yield significant improvement in slick detection and boundary definition.

Application of a passive polarimetric infrared sensor in improved detection and classification of targets

Automatic detection and recognition of targets by means of passive IR sensors suffer from limitations due to lack of sufficient contrast between the targets and their background, and among the facets of a target. In this paper the results of a suite of polarization-sensitive automatic target detection and recognition algorithms on sets of simulated and real polarimetric IR imagery are presented. A custom designed Polarimetric IR (PIR) imaging sensor is used for collecting real polarimetric target data-three of the four Stokes parameters under a variety of conditions. Then a set of novel algorithms are designed and tested that uses the target and background Stokes parameters for detection, segmentation and classification of targets. The empirical performance results are obtained in terms of the probabilities of detection, false alarm rate, segmentation accuracy, and recognition probabilities as functions of number of pixels on target, aspect and depression angles and under several background conditions (clutter densities) on the polarimetric and non-polarimetrirc data. These results show that a noticeable improvement over the non-polarimetric ATR can be achieved.

P-3 ultra-wideband SAR: description and examples

Under the Advanced Research Projects Agency (ARPA)/ASTO sponsorship, through a contract from the Naval Air Warfare Center (NAWC), the Environmental Research Institute of Michigan (ERIM) has developed an ultra-wideband (UWB) very high frequency (VHF)/ultrahigh frequency (UHF) fully polarimetric airborne synthetic aperture radar (SAR) for studying the detection of foliage-obscured objects. The radar is installed in the NAWC P-3 testbed aircraft and takes advantage of existing ERIM-built multimode, fully-polarimetric X/L/C-band SAR hardware. This paper describes the radar and presents some examples of its capabilities including polarimetric imagery and two-pass interferometric surface height estimates.

On the accuracy of crosstalk calibration of polarimetric SAR using natural clutter statistics

A method for the routine correction of fully polarimetric synthetic-aperture radar (SAR) images proposed by J.J. van Zyl (1990) uses assumed statistical properties of natural distributed targets. The method has the potential to improve dramatically the accuracy of polarimetric imagery contaminated by antenna crosstalk and may be of importance for future spaceborne polarimetric SARs as well as current airborne systems. The accuracy of the method is assessed when the statistics of clutter deviate from the assumed form, and limits are placed on likely acceptable deviations. These statistics are studied for a heterogeneous forestry and agricultural scene imaged by the NASA/JPL radar. The only significant deviations were found over certain man-made targets, including villages, and a single agricultural field. The results lend support to the routine use of the van Zyl method in such applications.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Techniques in processing multi-frequency multi-polarization spaceborne SAR data

This paper presents the algorithm design of the SIR-C ground data processor, with emphasis on the unique elements involved in the production of registered multifrequency polarimetric data products. A quick-look processing algorithm used for generation of low-resolution browse image products and estimation of echo signal parameters is also presented. Specifically the discussion covers: (1) azimuth reference function generation to produce registered polarimetric imagery; (2) geometric rectification to accommondate cross-track and along-track Doppler drifts; (3) multilook filtering designed to generate output imagery with a uniform resolution; and (4) efficient coding to compress the polarimetric image data for distribution.