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Physical Sciences and Mathematics Commons™
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Articles 1 - 7 of 7
Full-Text Articles in Physical Sciences and Mathematics
Enhanced Space Object Detection Without Prior Knowledge Of The Point Spread Function, Grant F. Graupmann
Enhanced Space Object Detection Without Prior Knowledge Of The Point Spread Function, Grant F. Graupmann
Theses and Dissertations
Since the point detector was created, other detection algorithms have been created that increase the probability of detection, while still keeping the same probability of false alarm. The point detector still has uses, such as when there is no prior knowledge of the point spread function (PSF). The matched filter correlator (MFC) detector is reliant on prior knowledge of the PSF. This has been an issue in cases where the PSF information is potentially inaccurate or unknown. This thesis utilizes MFC detector in a manner that it has never been used before, along with a new detection algorithm, the Pearson's …
Image Processing For Multiple-Target Tracking On A Graphics Processing Unit, Michael A. Tanner
Image Processing For Multiple-Target Tracking On A Graphics Processing Unit, Michael A. Tanner
Theses and Dissertations
Multiple-target tracking (MTT) systems have been implemented on many different platforms, however these solutions are often expensive and have long development times. Such MTT implementations require custom hardware, yet offer very little flexibility with ever changing data sets and target tracking requirements. This research explores how to supplement and enhance MTT performance with an existing graphics processing unit (GPU) on a general computing platform. Typical computers are already equipped with powerful GPUs to support various games and multimedia applications. However, such GPUs are not currently being used in desktop MTT applications. This research explores if and how a GPU can …
Determination Of Structure From Motion Using Aerial Imagery, Paul R. Graham
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 …
Concurrent Cognitive Mapping And Localization Using Expectation Maximization, Kennard R. Laviers
Concurrent Cognitive Mapping And Localization Using Expectation Maximization, Kennard R. Laviers
Theses and Dissertations
Robot mapping remains one of the most challenging problems in robot programming. Most successful methods use some form of occupancy grid for representing a mapped region. An occupancy grid is a two dimensional array in which the array cells represents (x,y) coordinates of a cartesian map. This approach becomes problematic in mapping large environments as the map quickly becomes too large for processing and storage. Rather than storing the map as an occupancy grid, our robot (equipped with ultrasonic sonars) views the world as a series of connected spaces. These spaces are initially mapped as an occupancy grid in a …
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 …
An Objective Evaluation Of Four Sar Image Segmentation Algorithms, Jason B. Gregga
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
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 …