Biomedical subjects

Firooz A Sadjadi

Publications and source records attributed to Firooz A Sadjadi.

6 recordsLinked to original sources

PubMed2007

Passive three-dimensional imaging using polarimetric diversity.

The results of experiments in developing a method for extracting three-dimensional information from a scene by means of a polarimetric passive imaging sensor are summarized. This sensor provides a full Stokes vector at each sensor pixel location from which degree and angle of linear polarization are computed. The angle of linear polarization provides the azimuth angle of the surface normal vector. The depression angle of this surface normal vector is obtained in terms of the emitting object's index of refraction from the solution of an equation derived from Fresnel equations, Snell's law, and percent of linear polarization. Results of the application of this approach to simulated infrared polarimetric data are provided.

Journal Article↗

PubMed2006

Adaptive polarimetric sensing for optimum radar signature classification using a genetic search algorithm.

An automated technique for adaptive radar polarimetric pattern classification is described. The approach is based on a genetic algorithm that uses a probabilistic pattern separation distance function and searches for those transmit and receive states of polarization sensing angles that optimize this function. Seven pattern separation distance functions--the Rayleigh quotient, the Bhattacharyya, divergence, Kolmogorov, Matusta, Kullback-Leibler distances, and the Bayesian probability of error--are used on real, fully polarimetric synthetic aperture radar target signatures. Each of these signatures is represented as functions of transmit and receive polarization ellipticity angles and the angle of polarization ellipse. The results indicate that, based on the majority of the distance functions used, there is a unique set of state of polarization angles whose use will lead to improved classification performance.

Journal Article↗

PubMed2006

Target-adaptive polarimetric synthetic aperture radar target discrimination using maximum average correlation height filters.

We report the development of a technique for adaptive selection of polarization ellipse tilt and ellipticity angles such that the target separation from clutter is maximized. From the radar scattering matrix [S] and its complex components, in phase and quadrature phase, the elements of the Mueller matrix are obtained. Then, by means of polarization synthesis, the radar cross section of the radar scatters are obtained at different transmitting and receiving polarization states. By designing a maximum average correlation height filter, we derive a target versus clutter distance measure as a function of four transmit and receive polarization state angles. The results of applying this method on real synthetic aperture radar imagery indicate a set of four transmit and receive angles that lead to maximum target versus clutter discrimination. These optimum angles are different for different targets. Hence, by adaptive control of the state of polarization of polarimetric radar, one can noticeably improve the discrimination of targets from clutter.

Journal Article↗

PubMed2005

Polarimetric laser radar target classification.

Imaging laser radar (ladar) systems have been developed for automatic target identification in surveillance systems. Ladar uses the range value at the target pixels to estimate the target's 3-D shape and identify the target. For targets in clutter and partially hidden targets, there are ambiguities in determining which pixels are on target that lead to uncertainties in determining the target's 3-D shape. An improvement is to use the polarization components of the reflected light. We describe the operation and preliminary evaluation of a polarization diverse imaging ladar system. Using a combination of intensity, range, and degree of polarization, we are better able to identify and distinguish the target from other objects of the same class.

Algorithms↗

PubMed2004

Infrared target detection with probability density functions of wavelet transform subbands.

We report the development of a wavelet multiresolution texture-based algorithm that uses the probability density functions (PDFs) of the subband of the wavelet decomposition of an image. The moments of these pdfs are used in a clustering algorithm to segment the targets from their background clutter. Using the tools of experimental methodology, we evaluate the performance of this algorithm on real infrared imagery under varying algorithm parameter sets as well as scene, image, and false-alarm conditions. We estimate a set of multidimensional predictive analytic performance models that relate the detection probabilities as functions of false alarm, algorithm internal parameter, target pixel number, target-to-background interference ratio, target-interference ratio, and Fechner-Weber and local entropy metrics in the scene. These models can be used to predict performance in regions were no data are available and to optimize performance by selection of the optimum parameter and constant false-alarm values in regions with known scene and metric conditions.

Journal Article↗

PubMed2003

Automatic detection of small objects from their infrared state-of-polarization vectors.

A technique for automatic detection of targets from their infrared signature's state-of-polarization vector is described. The bounds on the Bayesian total probability of errors are estimated from the observed Stokes vector imagery and used as metrics for separating targets from background clutter. The performance of the proposed approach for objects under various geometries is studied in terms of receiver operating characteristic curves. The new results, which have been obtained from data from the U.S. Air Force's Infrared Modeling and Analysis polarimetric infrared simulation tool, indicate the usefulness of polarimetric infrared signatures for the automatic detection of small targets.

Journal Article↗