Open Access. Powered by Scholars. Published by Universities.®

Signal Processing Commons

Open Access. Powered by Scholars. Published by Universities.®

Articles 1 - 9 of 9

Full-Text Articles in Signal Processing

Machine Learning Land Cover And Land Use Classification Of 4-Band Satellite Imagery, Lorelei Turner [*], Torrey J. Wagner, Paul Auclair, Brent T. Langhals Jan 2022

Machine Learning Land Cover And Land Use Classification Of 4-Band Satellite Imagery, Lorelei Turner [*], Torrey J. Wagner, Paul Auclair, Brent T. Langhals

Faculty Publications

Land-cover and land-use classification generates categories of terrestrial features, such as water or trees, which can be used to track how land is used. This work applies classical, ensemble and neural network machine learning algorithms to a multispectral remote sensing dataset containing 405,000 28x28 pixel image patches in 4 electromagnetic frequency bands. For each algorithm, model metrics and prediction execution time were evaluated, resulting in two families of models; fast and precise. The prediction time for an 81,000-patch group of predictions wasmodels, and >5s for the precise models, and there was not a significant change in prediction time when a …


Digital Holography Efficiency Experiments For Tactical Applications, Douglas E. Thornton Sep 2019

Digital Holography Efficiency Experiments For Tactical Applications, Douglas E. Thornton

Theses and Dissertations

Digital holography (DH) uses coherent detection and offers direct access to the complex-optical field to sense and correct image aberrations in low signal-to-noise environments, which is critical for tactical applications. The performance of DH is compared to a similar, well studied deep-turbulence wavefront sensor, the self-referencing interferometer (SRI), with known efficiency losses. Wave optics simulations with deep-turbulence conditions and noise were conducted and the results show that DH outperforms the SRI by 10's of dB due to DH's strong reference. Additionally, efficiency experiments were conducted to investigate DH system losses. The experimental results show that the mixing efficiency (37%) is …


Improving Detection Of Dim Targets: Optimization Of A Moment-Based Detection Algorithm, Shannon R. Young Dec 2018

Improving Detection Of Dim Targets: Optimization Of A Moment-Based Detection Algorithm, Shannon R. Young

Theses and Dissertations

Wide area motion imagery (WAMI) sensor technology is advancing rapidly. Increases in frame rates and detector array sizes have led to a dramatic increase in the volume of data that can be acquired. Without a corresponding increase in analytical manpower, much of these data remain underutilized. This creates a need for fast, automated, and robust methods for detecting dim, moving signals of interest. Current approaches fall into two categories: detect-before-track (DBT) and track-before-detect (TBD) methods. The DBT methods use thresholding to reduce the quantity of data to be processed, making real time implementation practical but at the cost of the …


The Effect Of Synthetic Aperture Radar Image Resolution On Target Discrimination, John E. Mcgowan Mar 2010

The Effect Of Synthetic Aperture Radar Image Resolution On Target Discrimination, John E. Mcgowan

Theses and Dissertations

This research details the effect of spatial resolution on target discrimination in Synthetic Aperture Radar (SAR) images. Multiple SAR image chips containing targets and non-targets are used to test a baseline Automatic Target Recognition (ATR) system with reduced spatial resolution. Spatial resolution is reduced by lowering the pixel count or synthesizing a degraded image by filtering and reducing the pixel count. A two-parameter Constant False Alarm Rate (CFAR) detector is tested, and three feature sets, size, contrast, and texture, are used to train a linear classifier and to estimate probability density functions for the two classes. The results are scored …


Abstracting Gis Layers From Hyperspectral Imagery, Torsten E. Howard Mar 2009

Abstracting Gis Layers From Hyperspectral Imagery, Torsten E. Howard

Theses and Dissertations

Modern warfare methods in the urban environment necessitates the use of multiple layers of sensors to manage the battle space. Hyperspectral imagers are one possible sensor modality to provide remotely sensed images that can be converted into Geographic Information Systems (GIS) layers. GIS layers abstract knowledge of roads, buildings, and scene content and contain shape files that outline and highlight scene features. Creating shape files is a labor-intensive and time-consuming process. The availability of shape files that reflect the current configuration of an area of interest significantly enhances Intelligence Preparation of the Battlespace (IPB). The solution presented in this thesis …


A Wide Area Bipolar Cascade Resonant Cavity Light Emitting Diode For A Hybrid Range-Intensity, Reginald J. Turner Jun 2008

A Wide Area Bipolar Cascade Resonant Cavity Light Emitting Diode For A Hybrid Range-Intensity, Reginald J. Turner

Theses and Dissertations

This dissertation focused on the development of an illuminator for the HRIS. This illuminator enables faster image rendering and reduces the potential of errors in return signal data, that could be generated from extremely rough terrain. Four major achievements resulted from this work, which advance the field of 3-D image acquisition. The first is that the TJ is an effective current spreading layer for LEDs with mesa width up to 140 micrometers and current densities of approximately 1 x 106 Amp/square centimeter. The TJ allows fabrication of an efficient illuminator, with required geometry for the HRIS to operate as …


Hyperspectral-Augmented Target Tracking, Neil A. Soliman Mar 2008

Hyperspectral-Augmented Target Tracking, Neil A. Soliman

Theses and Dissertations

With the global war on terrorism, the nature of military warfare has changed significantly. The United States Air Force is at the forefront of research and development in the field of intelligence, surveillance, and reconnaissance that provides American forces on the ground and in the air with the capability to seek, monitor, and destroy mobile terrorist targets in hostile territory. One such capability recognizes and persistently tracks multiple moving vehicles in complex, highly ambiguous urban environments. The thesis investigates the feasibility of augmenting a multiple-target tracking system with hyperspectral imagery. The research effort evaluates hyperspectral data classification using fuzzy c-means …


Phase Diversity And Polarization Augmented Techniques For Active Imaging, Peter M. Johnson Mar 2007

Phase Diversity And Polarization Augmented Techniques For Active Imaging, Peter M. Johnson

Theses and Dissertations

A multi-frame active phase diversity imaging (APDI) algorithm is derived for coherent light statistics and demonstrated. In addition to conventional focal-plane and diversity-plane data, a statistical description for pupil-plane (PP) intensity is formed and included in the derivation. The algorithm is implemented and characterized via Monte Carlo simulation. Analysis shows that it's robust, insensitive to detection noise for SNR ? 7, performs well for SNR's as low as 2, and that the effect of system configuration on optimal parameters is minimal. Furthermore, introduction of PP data results in a 60% better reconstruction from dynamically aberrated data than obtained using only …


Reconstruction Of Chromotomographic Imaging System Infrared Hyperspectral Scenes, Malcolm G. Gould Mar 2005

Reconstruction Of Chromotomographic Imaging System Infrared Hyperspectral Scenes, Malcolm G. Gould

Theses and Dissertations

Hyperspectral imagery providing both spatial and spectral information has diverse applications in remote sensing and scientific imaging scenarios. The development of the Chromotomographic Imaging System (CTIS) allows simultaneous collection of both spatial and spectral data by a two-dimensional (2D) focal plane detector array. Post-processing of the 2D detector data reconstructs the three-dimensional (3D) hyperspectral content of the imaged scene. This thesis develops Estimation Theory based algorithms for reconstructing the hyperspectral scene data. The initial algorithm developed reconstructs the 3D hyperspectral scene data cube. An additional algorithm reconstructs a matrix comprised of one spectral dimension and one compound spatial dimension. This …