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Air Force Institute of Technology

1994

Articles 1 - 12 of 12

Full-Text Articles in Signal Processing

Perceptual Based Image Fusion With Applications To Hyperspectral Image Data, Terry A. Wilson Dec 1994

Perceptual Based Image Fusion With Applications To Hyperspectral Image Data, Terry A. Wilson

Theses and Dissertations

Development of new imaging sensors has created a need for image processing techniques that can fuse images from different sensors or multiple images produced by the same sensor. The methods presented here focus on combining image data from the Airborne Visual and Infrared Imaging Spectrometer (AVIRIS) hyperspectral sensor into a single or smaller subset of images while maintaining the visual information necessary for human analysis. Three hierarchical multi-resolution image fusion techniques are implemented and tested using the AVIRIS image data and test images that contain various levels of correlated or uncorrelated noise. Two of the algorithms are published fusion methods …

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Multipoint Multirate Signal Processing, Roger L. Claypoole Jr. Dec 1994

Multipoint Multirate Signal Processing, Roger L. Claypoole Jr.

Theses and Dissertations

This thesis provides a fundamentally new, systematic study of multipoint multirate signal processing systems. The multipoint multirate operators are analyzed via equivalent circuits comprised entirely of conventional multirate operators. Interconnections of the operators are demonstrated, and the multipoint noble identities are derived. The multipoint polyphase representation is presented, and the M channel multipoint multirate system with vector length N is presented as an MN channel multipoint polyphase system. The conditions sufficient for perfect reconstruction in the multipoint multirate system are derived. These conditions constrain the multipoint filter banks to be composed of comb filters generated from paraunitary sets of conventional …

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Processing Of Wide-Angle Synthetic Aperture Radar Signals For Detection Of Obscured Ground Targets, Richard J. Sumner Dec 1994

Processing Of Wide-Angle Synthetic Aperture Radar Signals For Detection Of Obscured Ground Targets, Richard J. Sumner

Theses and Dissertations

This thesis investigates advanced processing techniques for the detection of radar targets in the presence of clutter. It is assumed that the radar data available consist of multi-aspect angle, fully polarimetric Synthetic Aperture Radar (SAR) images. Various techniques are introduced and tested on available SAR data. These techniques attempt to exploit the multi-aspect angles in order to extract target characteristics not available in any single image. SAR images are manipulated in such a way to decrease the probability of false alarms in the target detection process. Target detection performance of the techniques is presented and compared. The techniques are shown …

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Multispectral Detection Of Ground Targets In Highly Correlated Backgrounds, Jason E. Thomas Dec 1994

Multispectral Detection Of Ground Targets In Highly Correlated Backgrounds, Jason E. Thomas

Theses and Dissertations

Multispectral detection methods attempt to discriminate targets in a dominant clutter background using multiple images of the same real-world scene taken in different narrow spectral bands in the infrared. Detection is possible due to the empirically observed phenomenon that the radiance of man-made objects, such as a tank or truck, often lies off the main spectral correlation axis of that of natural backgrounds. Radiometric measurements of several vehicles and a tree canopy background taken over three days in June. 1994 were used to examine the factors affecting multispectral detection. Results clearly showed that the processes which provide for higher spectral …

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Compensated Deconvolution From Wavefront Sensing, Lori A. Thorson Dec 1994

Compensated Deconvolution From Wavefront Sensing, Lori A. Thorson

Theses and Dissertations

The U.S. Air Force has a continuing mission to obtain imagery of earth-orbiting objects. One of the means for obtaining this imagery is through the use of ground-based observatories. A fundamental problem associated with imaging objects through the atmosphere is that atmospheric turbulence inflicts a large, random aberration on the telescope which effectively limits the realizable resolution to that of a much smaller telescope. Several approaches have been taken to overcome these effects including pure post processing, pure adaptive optics, and hybrid techniques involving both adaptive optics and image post processing. One key result from past approaches is that partially …

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Voice Analysis Using The Bispectrum, Deborah A. Douglass Dec 1994

Voice Analysis Using The Bispectrum, Deborah A. Douglass

Theses and Dissertations

The theory of the bispectrum has been studied, though very few practical applications have yet been considered in any depth. One application mentioned in the literature is the use of the bispectrum for voice signal processing. The aim of this thesis was to research the bispectrum towards the particular application of speech enhancement. The technique is based on the fact that the bispectrum is zero for a Gaussian white noise signal, arid the bispectrum of two signals added together is the sum of the two signal bispectra. Theoretically, processing signals in the bispectra domain should increase the signal-to-noise ratio of …

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Spatio-Temporal Pattern Recognition Using Hidden Markov Models, Kenneth H. Fielding Jun 1994

Spatio-Temporal Pattern Recognition Using Hidden Markov Models, Kenneth H. Fielding

Theses and Dissertations

A new spatio-temporal method for identifying 3D objects found in 2D image sequences is presented. The Hidden Markov Model technique is used as a spatio-temporal classification algorithm to identify 3D objects by the temporal changes in observed shape features. A new information theoretic argument is developed that proves identifying objects based on image sequences can lead to higher classification accuracies than single look methods. A new distance measure is proposed that analyzes the performance of Hidden Markov Models in a multi-class pattern recognition problem. A three class problem identifying moving light display objects provides experimental verification of the sequence processing …

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A Diffraction-Based Model Of Anisoplanatism Effects In Adaptive Optic Systems, Steven E. Troxel Jun 1994

A Diffraction-Based Model Of Anisoplanatism Effects In Adaptive Optic Systems, Steven E. Troxel

Theses and Dissertations

This dissertation presents a new model for computing the angle dependent performance measures of an adaptive-optics system. By incorporating diffraction caused by the index-of-refraction variations of the atmosphere, the phase and amplitude fluctuations of the propagating wave are computed. New theory is presented, that uses the diffraction-based propagation model to yield optical transfer function (OTF) expressions that are more accurate as compared to current theory that neglects diffraction. An evaluation method for calculating the OTF is presented that utilizes a layered atmospheric model and normalized OTF expressions. The diffraction model is also used to present the first OTF signal-to-noise ratio …

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Noise Reduction For Speech Enhancement Using Non-Linear Wavelet Processing, Hassan Dehmani Jun 1994

Noise Reduction For Speech Enhancement Using Non-Linear Wavelet Processing, Hassan Dehmani

Theses and Dissertations

The problem of speech enhancement presents many obstacles in the speech processing field. This thesis develops several speech de-noising systems that can be used in the time, fourier, and wavelet domains. We present two thresholding techniques soft and hard. The application of these thresholding techniques to noisy speech data is discussed. The combination of both wavelets and the Fourier domains with noisy phase restoration proves to yield the best results in terms of intelligibility. Informal listening tests were conducted in order to compare the effects and differences between the speech de-noising systems.

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Multirate Time-Frequency Distributions, John R. O'Hair May 1994

Multirate Time-Frequency Distributions, John R. O'Hair

Theses and Dissertations

Multirate systems, which find application in the design and analysis of filter banks, are demonstrated to also be useful as a computational paradigm. It is shown that any problem which can be expressed a set of vector-vector, matrix-vector or matrix-matrix operations can be recast using multirate. This means all of numerical linear algebra can be recast using multirate as the underlying computational paradigm. As a non-trivial example, the multirate computational paradigm is applied to the problem of Generalized Discrete Time- Frequency Distributions GDTFD to create a new family of fast algorithms. The first of this new class of distributions is …

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Feasibility Analysis For Predicting A Kinetic Kill Zone For Aircraft Homing Missile Defense, Mark E. Ennis Mar 1994

Feasibility Analysis For Predicting A Kinetic Kill Zone For Aircraft Homing Missile Defense, Mark E. Ennis

Theses and Dissertations

An extended Kalman filter is used to predict a kinetic kill zone for use in aircraft self defense versus homing missiles. The analysis is limited to an in-the-plane analysis and focuses on finding the model parameters which have the largest impact on the predicted kill zone. No attempt is made to optimize the design of the filter model itself. The analysis computes the kill zone relative to an assumed aircraft trajectory using strictly filter computed statistics. No Monte-Carlo simulations are used throughout the thesis. The filter assumed to be on the evading aircraft, uses an onboard laser radar (ladar) to …

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Clustering Techniques In Speaker Recognition, Douglas N. Prescott Mar 1994

Clustering Techniques In Speaker Recognition, Douglas N. Prescott

Theses and Dissertations

This thesis presents a comparison based on identification rate, of three clustering techniques applied to cepstral features for speaker identification. LBG vector quantization as developed by Linde, Buzo and Gray; is used to provide benchmark performance for comparison with Fuzzy clustering (based on the unsupervised fuzzy partition-optimal number of classes, UFP-ONC algorithm by Gath and Geva) and an Artificial Neural Network, the Multilayer Perceptron. Cepstral features from the TIMIT, King and AFIT93 corpus speaker databases are used to produce speaker-identification classifiers using each of the clustering algorithms. The experiment reported evaluates the speaker identification performance using the 20-dimensional cepstral features …

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