Engineering Commons^™

New Methods In Wavelet Analysis For Applications Of The Wavelet Transform, Jeffrey D. Williams

Theses and Dissertations

A commonality in the many applications and domains where signal processing (SP)is applied is the detection of events. Detection in SP requires the identification of the occurrence of an event, within a signal, and distinguishing the occurrence from no event. In a classical application of SP, seismologists seek to detect abnormalities in an electromagnetic (EM) signal to detect or not detect the occurrence of an earthquake, represented as an anomalous EM pulse. Since many signals are noisy, such as those produced by a seismograph, it can be challenging to distinguish a significant EM pulse from incident noise. In SP, smoothing …

Optical Study Of 2-D Detonation Wave Stability, Eulaine T. Grodner

Theses and Dissertations

Fundamental optical detonation study of detonations constricted to a 2-d plane propagation, and detonations propagating around a curve. All images were processed using modern image processing techniques. The optical techniques used were shadowgraph, Schlieren, and chemiluminescence. In the 2-Dstraight channels, it was determined wave stability was a factor of cell size. It was also determined the detonation wave thickness (area between the combustion and shockwave) was a factor of how much heat available for the detonation. For the detonations propagating around a curve, it was determined the three main classifications of wave stability were stable, unstable, and detonation wave restart. …

Atmospheric Turbulence Distortion In Video: Restoration Utilizing Sparse Analysis, Benjamin J. Sanda

Dissertations

The removal of atmospheric turbulence (AT) distortion in long range imaging is one of the most challenging areas of research in imaging processing with an immediate need for solutions in several applications such as in military and transportation systems. AT exacerbates distortion due to non-linear geometric blur and scintillations in long-distance images and videos, severely reducing image quality and information interpretation. AT negatively impacts both human and computer vision systems, compromising visibility essential for accurate object identification and tracking.

In this dissertation, a novel sparse analysis framework is developed to address efficient AT blur and scintillation removal in video. Operating …

Video And Image Super-Resolution Via Deep Learning With Attention Mechanism, Xuan Xu

Graduate Theses, Dissertations, and Problem Reports

Image demosaicing, image super-resolution and video super-resolution are three important tasks in color imaging pipeline. Demosaicing deals with the recovery of missing color information and generation of full-resolution color images from so-called Color filter Array (CFA) such as Bayer pattern. Image super-resolution aims at increasing the spatial resolution and enhance important structures (e.g., edges and textures) in super-resolved images. Both spatial and temporal dependency are important to the task of video super-resolution, which has received increasingly more attention in recent years. Traditional solutions to these three low-level vision tasks lack generalization capability especially for real-world data. Recently, deep learning methods …

Target Detection, Tracking, And Localization Using Multi-Spectral Image Fusion And Rf Doppler Differentials, Casey D. Demars

Dissertations, Master's Theses and Master's Reports

It is critical for defense and security applications to have a high probability of detection and low false alarm rate while operating over a wide variety of conditions. Sensor fusion, which is the the process of combining data from two or more sensors, has been utilized to improve the performance of a system by exploiting the strengths of each sensor. This dissertation presents algorithms to fuse multi-sensor data that improves system performance by increasing detection rates, lowering false alarms, and improving track performance. Furthermore, this dissertation presents a framework for comparing algorithm error for image registration which is a critical …

Image Processing And Understanding Based On Graph Similarity Testing: Algorithm Design And Software Development, Jieqi Kang

Doctoral Dissertations

Image processing and understanding is a key task in the human visual system. Among all related topics, content based image retrieval and classification is the most typical and important problem. Successful image retrieval/classification models require an effective fundamental step of image representation and feature extraction. While traditional methods are not capable of capturing all structural information on the image, using graph to represent the image is not only biologically plausible but also has certain advantages. Graphs have been widely used in image related applications. Traditional graph-based image analysis models include pixel-based graph-cut techniques for image segmentation, low-level and high-level image …

Geosynchronous Binary Object Detection, Patrick B. Cunningham

Theses and Dissertations

This paper will compare competing methods for optically detecting binary objects. This is mostly intended for use in Space Situational Awareness (SSA), though has the potential to be used in other applications. The first method referred to as, “Single Object Detection” is a versatile algorithm which is currently used to detect extraterrestrial objects. However, it does not take into account interference by a nearby object. Therefore a second algorithm is investigated, referred to as “Binary Object Detection”, which does. The binary detection algorithm proved to have a comparable or superior Receiver Operating Characteristic (ROC) curve (based upon the area under …

Automated Image Interpretation For Science Autonomy In Robotic Planetary Exploration, Raymond Francis

Electronic Thesis and Dissertation Repository

Advances in the capabilities of robotic planetary exploration missions have increased the wealth of scientific data they produce, presenting challenges for mission science and operations imposed by the limits of interplanetary radio communications. These data budget pressures can be relieved by increased robotic autonomy, both for onboard operations tasks and for decision- making in response to science data.

This thesis presents new techniques in automated image interpretation for natural scenes of relevance to planetary science and exploration, and elaborates autonomy scenarios under which they could be used to extend the reach and performance of exploration missions on planetary surfaces.

Two …

Enhanced Sonar Array Target Localization Using Time-Frequency Interference Phenomena, Jordan Almon Shibley

Dissertations and Theses

The ability of traditional active sonar processing methods to detect targets is often limited by clutter and reverberation from ocean environments. Similarly, multipath arrivals from radiating sources such as ships and submarines are received at sensors in passive sonar systems. Reverberation and multipath signals introduce constructive and destructive interference patterns in received spectrograms in both active and passive sonar applications that vary with target range and frequency. The characterization and use of interference phenomena can provide insights into environmental parameters and target movement in conjunction with standard processing methods including spectrograms and array beamforming.

This thesis focuses on utilizing the …

Spectral Detection Of Human Skin In Vis-Swir Hyperspectral Imagery Without Radiometric Calibration, Andrew P. Beisley

Theses and Dissertations

Many spectral detection algorithms require precise ground truth measurements that are hand-selected in the image to apply radiometric calibration, converting image pixels into estimated reflectance vectors. That process is impractical for mobile, real-time hyperspectral target detection systems, which cannot empirically derive a pixel-to-reflectance relationship from objects in the image. Implementing automatic target recognition on high-speed snapshot hyperspectral cameras requires the ability to spectrally detect targets without performing radiometric calibration. This thesis demonstrates human skin detection on hyperspectral data collected at a high frame rate without using calibration panels, even as the illumination in the scene changes. Compared to an established …

Three-Dimensional Target Modeling With Synthetic Aperture Radar, John R. Hupton

Master's Theses

Conventional Synthetic Aperture Radar (SAR) offers high-resolution imaging of a target region in the range and cross-range dimensions along the ground plane. Little or no data is available in the range-altitude dimension, however, and target functions and models are limited to two-dimensional images. This thesis first investigates some existing methods for the computation of target reflectivity data in the deficient elevation domain, and a new method is then proposed for three-dimensional (3-D) SAR target feature extraction.

Simulations are implemented to test the decoupled least-squares technique for high-resolution spectral estimation of target reflectivity, and the accuracy of the technique is assessed. …

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 …

Multi-Reference Frame Image Registration For Rotation, Translation, And Scale, Christopher S. Costello

Theses and Dissertations

This thesis investigates applications of multi-reference frame image registration for image sets with various translation, rotation, and scale combinations. It focuses on registration accuracy improvement over traditional pairwise registration, and also compares the quality of scene estimation from frame averaging. Three experiments are developed which use cross-correlation to estimate translation, the Radon transform to estimate translation and rotation, and the Fourier-Mellin transform to estimate translation, rotation, and scale. Results from applying multi-reference frame registration in these experiments show distinct improvements in both registration accuracy and quality of frame averaging compared to single-reference frame registration. Furthermore, it is shown that the …

Fusion Of Imaging And Inertial Sensors For Navigation, Michael J. Veth

Theses and Dissertations

The motivation of this research is to address the limitations of satellite-based navigation by fusing imaging and inertial systems. The research begins by rigorously describing the imaging and navigation problem and developing practical models of the sensors, then presenting a transformation technique to detect features within an image. Given a set of features, a statistical feature projection technique is developed which utilizes inertial measurements to predict vectors in the feature space between images. This coupling of the imaging and inertial sensors at a deep level is then used to aid the statistical feature matching function. The feature matches and inertial …

Fast Video Stabilization Algorithms, Mohammed A. Alharbi

Theses and Dissertations

A fast and robust electronic video stabilization algorithm is presented in this thesis. It is based on a two-dimensional feature-based motion estimation technique. The method tracks a small set of features and estimates the movement of the camera between consecutive frames. It is used to characterize the motions accurately including camera rotations between two imaging instants. An affine motion model is utilized to determine the parameters of translation and rotation between images. The determined affine transformation is then exploited to compensate for the abrupt temporal discontinuities of input image sequences. Also, a frequency domain approach is developed to estimate translations …

Image Processing Resource Allocation Methods For Multi-Target Tracking Of Dismounted Targets In Urban Environments, Jonathan P. Champion

Theses and Dissertations

Dismounted targets can be tracked in urban environments with video sensors. Real-time systems are unable to process all of the imagery, demanding some method for prioritization of the processing resources. Furthermore, various segmentation algorithms exist within image processing, each algorithm possesses unique capabilities, and each algorithm has an associated computational cost. Additional complexity arises in the prioritization problem when targets become occluded (e.g., by a building) and when the targets are intermixed with other dismounted entities. This added complexity leads to the question "which portions of the scene warrant both low cost and high cost processing?" The approach presented in …

Wide-Angle Multistatic Synthetic Aperture Radar: Focused Image Formation And Aliasing Artifact Mitigation, Jonathan E. Luminati

Theses and Dissertations

Traditional monostatic Synthetic Aperture Radar (SAR) platforms force the user to choose between two image types: larger, low resolution images or smaller, high resolution images. Switching to a Wide-Angle Multistatic Synthetic Aperture Radar (WAM-SAR) approach allows formation of large high-resolution images. Unfortunately, WAM-SAR suffers from two significant implementation problems. First, wavefront curvature effects, non-linear flight paths, and warped ground planes lead to image defocusing with traditional SAR processing methods. A new 3-D monostatic/bistatic image formation routine solves the defocusing problem, correcting for all relevant wide-angle effects. Inverse SAR (ISAR) imagery from a Radar Cross Section (RCS) chamber validates this approach. …

Optimization Of Automatic Target Recognition With A Reject Option Using Fusion And Correlated Sensor Data, Trevor I. Laine

Theses and Dissertations

This dissertation examines the optimization of automatic target recognition (ATR) systems when a rejection option is included. First, a comprehensive review of the literature inclusive of ATR assessment, fusion, correlated sensor data, and classifier rejection is presented. An optimization framework for the fusion of multiple sensors is then developed. This framework identifies preferred fusion rules and sensors along with rejection and receiver operating characteristic (ROC) curve thresholds without the use of explicit misclassification costs as required by a Bayes' loss function. This optimization framework is the first to integrate both "vertical" warfighter output label analysis and "horizontal" engineering confusion matrix …

Determination Of Structure From Motion Using Aerial Imagery, Paul R. Graham

Theses and Dissertations

The structure from motion process creates three-dimensional models from a sequence of images. Until recently, most research in this field has been restricted to land-based imagery. This research examines the current methods of land-based structure from motion and evaluates their performance for aerial imagery. Current structure from motion algorithms search the initial image for features to track though the subsequent images. These features are used to create point correspondences between the two images. The correspondences are used to estimate the motion of the camera and then the three-dimensional structure of the scene. This research tests current algorithms using synthetic data …

Utilizing Near-Field Measurements To Characterize Far-Field Radar Signatures, John R. Watkins

Theses and Dissertations

The increased need for stealth aircraft requires an on-site Far-Field (FF) Radar Cross-Section (RCS) measurement process. Conducting these measurements in on-site Near-Field (NF) monostatic facilities results in significant savings for manufacturers and acquisition programs. However, NF measurements are not directly extended to a FF RCS. Therefore, a large target Near-Field to Far-Field Transformation (NFFFT) is needed for RCS measurements. One approach requires an Inverse Synthetic Aperture Radar (ISAR) process to create accurate scattering maps. The focus of this work is the development of accurate NF scattering maps generated by a monostatic ISAR process. As a first look, the process is …

Classification Of Radar Targets Using Invariant Features, Gregory J. Meyer

Theses and Dissertations

Automatic target recognition ATR using radar commonly relies on modeling a target as a collection of point scattering centers, Features extracted from these scattering centers for input to a target classifier may be constructed that are invariant to translation and rotation, i.e., they are independent of the position and aspect angle of the target in the radar scene. Here an iterative approach for building effective scattering center models is developed, and the shape space of these models is investigated. Experimental results are obtained for three-dimensional scattering centers compressed to nineteen-dimensional feature sets, each consisting of the singular values of the …

Fast Compression Of Imagery With High Frequency Content, D. Scott Anderson

Theses and Dissertations

Image compression is an active area due to the many applications involving electronic media. Much research has been focused on image quality versus bit rate and/or algorithm speed. Here, we seek an effective image coder with a weighted constraint on speed. However, the compression must not taint the quality of impulsive features on the image. Moreover, the camera is operated in a mode that creates a dominant fixed pattern noise across the image array, degrading visual quality and disrupting compression performance. We propose a method that efficiently compresses such an image. We begin by characterizing and removing the fixed pattern …

Redundant Discrete Wavelet Transform Based Super-Resolution Using Sub-Pixel Image Registration, Daniel L. Ward

Theses and Dissertations

The limited resolution of video imagery taken by aircraft, over geographical areas of interest, hinders the accurate extraction of useful information. The frame resolution of the video is determined by the camera that created it. Information exists about the camera which can be used to increase frame resolution beyond the resolution capability of the camera. This is achieved by a process called super-resolution, which uses multiple low-resolution video frames to create one high-resolution image.

Feature Guided Image Registration Applied To Phase And Wavelet-Base Optic Flow, Kate R. Duffy

Theses and Dissertations

Optic Flow algorithms are useful in problems such as computers vision, navigational systems, and robotics. However, current algorithms are computationally expensive or lack the accuracy to be effective compared with traditionally navigation systems. Recently, lower accuracy inertial navigation systems (INS) based on Microelectromechanical systems (MEMS) technology have been proposed to replace more accurate traditional navigation systems.

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 …

Image Registration Using Redundant Wavelet Transforms, Richard K. Brown

Theses and Dissertations

Imagery is collected much faster and in significantly greater quantities today compared to a few years ago. Accurate registration of this imagery is vital for comparing the similarities and differences between multiple images. Since human analysis is tedious and error prone for large data sets, we require an automatic, efficient, robust, and accurate method to register images. Wavelet transforms have proven useful for a variety of signal and image processing tasks, including image registration. In our research, we present a fundamentally new wavelet-based registration algorithm utilizing redundant transforms and a masking process to suppress the adverse effects of noise and …

An Objective Evaluation Of Four Sar Image Segmentation Algorithms, Jason B. Gregga

Theses and Dissertations

Because of the large number of SAR images the Air Force generates and the dwindling number of available human analysts, automated methods must be developed. A key step towards automated SAR image analysis is image segmentation. There are many segmentation algorithms, but they have not been tested on a common set of images, and there are no standard test methods. This thesis evaluates four SAR image segmentation algorithms by running them on a common set of data and objectively comparing them to each other and to human segmentors. This objective comparison uses a multi-metric a approach with a set of …

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 …

The Role Of Frame Selection And Bispectrum Phase Reconstruction For Speckle Imaging Through Atmospheric Turbulence, Elizabeth A. Harpold

Theses and Dissertations

Frame selection using quality sharpness metrics have been shown in previous AFIT theses, to be effective in improving the final product of images obtained using adaptive optics. This thesis extends this idea to noncompensated speckle image data. Speckle image reconstruction is simulated with and without frame selection. Speckle images require the processing of hundreds of data frames. Frame selection is a method of reducing the amount of data required to reconstruct the image. A collection of short exposure image data frames of a single object are sorted based on sharpness metrics. Only the highest quality frames are retained and processed …

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 …