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Full-Text Articles in Signal Processing
Blind Deconvolution Through Polarization Diversity Of Long Exposure Imagery, Steven P. James
Blind Deconvolution Through Polarization Diversity Of Long Exposure Imagery, Steven P. James
Theses and Dissertations
The purpose of the algorithm developed in this thesis was to create a post processing method that could resolve objects at low signal levels using polarization diversity and no knowledge of the atmospheric seeing conditions. The process uses a two-channel system, one unpolarized image and one linearly polarized image, in a GEM algorithm to reconstruct the object. Previous work done by Strong showed that a two-channel system using polarization diversity on short exposure imagery could produce images up to twice the diffraction limit. In this research, long exposure images were simulated and a simple Kolmogorov model used. This allowed for …
Polarimeter Blind Deconvolution Using Image Diversity, David M. Strong
Polarimeter Blind Deconvolution Using Image Diversity, David M. Strong
Theses and Dissertations
This research presents an algorithm that improves the ability to view objects using an electro-optical imaging system with at least one polarization sensitive channel in addition to the primary channel. An innovative algorithm for detection and estimation of the defocus aberration present in an image is also developed. Using a known defocus aberration, an iterative polarimeter deconvolution algorithm is developed using a generalized expectation-maximization (GEM) model. The polarimeter deconvolution algorithm is extended to an iterative polarimeter multiframe blind deconvolution (PMFBD) algorithm with an unknown aberration. Using both simulated and laboratory images, the results of the new PMFBD algorithm clearly outperforms …
Multiframe Shift Estimation, Stephen A. Bruckart
Multiframe Shift Estimation, Stephen A. Bruckart
Theses and Dissertations
The purpose of this research was to develop a fundamental framework for a new approach to multiframe translational shift estimation in image processing. This thesis sought to create a new multiframe shift estimator, to theoretically prove and experimentally test key properties of it, and to quantify its performance according to several metrics. The new estimator was modeled successfully and was proven to be an unbiased estimator under certain common image noise conditions. Furthermore its performance was shown to be superior to the cross correlation shift estimator, a robust estimator widely used in similar image processing cases, according to several criteria. …
Translation And Rotation Invariant Multiscale Image Registration, Jennifer L. Manfra
Translation And Rotation Invariant Multiscale Image Registration, Jennifer L. Manfra
Theses and Dissertations
The most recent research involved registering images in the presence of translations and rotations using one iteration of the redundant discrete wavelet transform. We extend this work by creating a new multiscale transform to register two images with translation or rotation differences, independent of scale differences between the images. Our two-dimensional multiscale transform uses an innovative combination of lowpass filtering and the continuous wavelet transform to mimic the two-dimensional redundant discrete wavelet transform. This allows us to obtain multiple subbands at various scales while maintaining the desirable properties of the redundant discrete wavelet transform. Whereas the discrete wavelet transform produces …
Ultra-Wideband Tem Horns, Transient Arrays And Exponential Curves: A Fdtd Look, Troy S. Utton
Ultra-Wideband Tem Horns, Transient Arrays And Exponential Curves: A Fdtd Look, Troy S. Utton
Theses and Dissertations
This research investigates the possibility of applying exponentially curved conducting plates to single-element Transverse Electromagnetic (TEM) horns and their transient arrays to enhance the UWB characteristics already experienced by these radiators. The first part of this study demonstrates the Finite-Difference Time-Domain (FDTD) method's ability to duplicate experimental data, and establishes the baseline models used throughout the remainder of the research. The baseline models consist of the typical flat-triangle shaped conducting plates. The exponential taper models incorporate the exponential curves in the height, the width, and both the height and width directions. One, two- and four-element baseline configurations are compared to …
Automatic Target Cueing Of Hyperspectral Image Data, Terry A. Wilson
Automatic Target Cueing Of Hyperspectral Image Data, Terry A. Wilson
Theses and Dissertations
Modern imaging sensors produce vast amounts data, overwhelming human analysts. One such sensor is the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) hyperspectral sensor. The AVIRIS sensor simultaneously collects data in 224 spectral bands that range from 0.4µm to 2.5µm in approximately 10nm increments, producing 224 images, each representing a single spectral band. Autonomous systems are required that can fuse "important" spectral bands and then classify regions of interest if all of this data is to be exploited. This dissertation presents a comprehensive solution that consists of a new physiologically motivated fusion algorithm and a novel Bayes optimal self-architecting classifier …
Representations, Approximations, And Algorithms For Mathematical Speech Processing, Laura R. Suzuki
Representations, Approximations, And Algorithms For Mathematical Speech Processing, Laura R. Suzuki
Theses and Dissertations
Representing speech signals such that specific characteristics of speech are included is essential in many Air Force and DoD signal processing applications. A mathematical construct called a frame is presented which captures the important time-varying characteristic of speech. Roughly speaking, frames generalize the idea of an orthogonal basis in a Hilbert space, Specific spaces applicable to speech are L2(R) and the Hardy spaces Hp(D) for p> 1 where D is the unit disk in the complex plane. Results are given for representations in the Hardy spaces involving Carleson's inequalities (and its extensions), …
Atmospheric Induced Errors In Space-Time Adaptive Processing, Vinod D. Naga
Atmospheric Induced Errors In Space-Time Adaptive Processing, Vinod D. Naga
Theses and Dissertations
This thesis examines the effects of atmospheric turbulence-induced phase perturbations on the performance of ground-based Space-Time Adaptive Processing (STAP) systems. Both Fully Adaptive Joint Domain Optimum and Partially Adaptive Factored-Time Space processing methods are examined. This thesis concentrates on the turbulence effects on STAP applied to ground-based arrays. This thesis further focuses on the capability of STAP to resolve targets at low elevation angles in the presence of turbulence. Only clutter interference and receiver noise are considered. Turbulence effects on the EM phase-front are calculated for turbulence strength Cn(2) values ranging from 5.0 x 10(exp -14) m-2/3 to 5.0 x …
Applications Of Unsupervised Clustering Algorithms To Aircraft Identification Using High Range Resolution Radar, Dzung Tri Pham
Applications Of Unsupervised Clustering Algorithms To Aircraft Identification Using High Range Resolution Radar, Dzung Tri Pham
Theses and Dissertations
Identification of aircraft from high range resolution (HRR) radar range profiles requires a database of information capturing the variability of the individual range profiles as a function of viewing aspect. This database can be a collection of individual signatures or a collection of average signatures distributed over the region of viewing aspect of interest. An efficient database is one which captures the intrinsic variability of the HRR signatures without either excessive redundancy typical of single-signature databases, or without the loss of information common when averaging arbitrary groups of signatures. The identification of 'natural' clustering of similar HRR signatures provides a …