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Articles 1 - 4 of 4
Full-Text Articles in Optics
Anomaly Detection In Hyperspectral Imagery: Comparison Of Methods Using Diurnal And Seasonal Data, Patrick C. Hytla, Russell C. Hardie, Michael T. Eismann, Joseph Meola
Anomaly Detection In Hyperspectral Imagery: Comparison Of Methods Using Diurnal And Seasonal Data, Patrick C. Hytla, Russell C. Hardie, Michael T. Eismann, Joseph Meola
Electrical and Computer Engineering Faculty Publications
The use of hyperspectral imaging is a fast growing field with many applications in the civilian, commercial and military sectors. Hyperspectral images are typically composed of many spectral bands in the visible and infrared regions of the electromagnetic spectrum and have the potential to deliver a great deal of information about a remotely sensed scene. One area of interest regarding hyperspectral images is anomaly detection, or the ability to find spectral outliers within a complex background in a scene with no a priori information about the scene or its specific contents. Anomaly detectors typically operate by creating a statistical background …
Scene-Based Nonuniformity Correction With Reduced Ghosting Using A Gated Lms Algorithm, Russell C. Hardie, Frank Orion Baxley, Brandon J. Brys, Patrick C. Hytla
Scene-Based Nonuniformity Correction With Reduced Ghosting Using A Gated Lms Algorithm, Russell C. Hardie, Frank Orion Baxley, Brandon J. Brys, Patrick C. Hytla
Electrical and Computer Engineering Faculty Publications
In this paper, we present a scene-based nouniformity correction (NUC) method using a modified adaptive least mean square (LMS) algorithm with a novel gating operation on the updates. The gating is designed to significantly reduce ghosting artifacts produced by many scene-based NUC algorithms by halting updates when temporal variation is lacking. We define the algorithm and present a number of experimental results to demonstrate the efficacy of the proposed method in comparison to several previously published methods including other LMS and constant statistics based methods. The experimental results include simulated imagery and a real infrared image sequence. We show that …
Evaluation Of Performance Of A Maximum Likelihood Estimator For Tracking Purposes In The Presence Of Speckle Noise, Adrian Brett Monz
Evaluation Of Performance Of A Maximum Likelihood Estimator For Tracking Purposes In The Presence Of Speckle Noise, Adrian Brett Monz
Theses and Dissertations
In many cases, optical tracking systems do not have cooperative beacons avail- able. This is particularly true for the case involving tracking a laser illuminated target such as a missile seeker head, where the object of interest is an extended source. Furthermore the extended source is often observed in the presence of noise such as shot and speckle noise as well as atmospheric turbulence which further degrades the signal. This research effort presents the evaluation of an existing algorithm based on the maximum-likelihood technique for tilt estimation in the presence of extended sources and speckle noise, with particular application to …
Imaging Reconstruction For Light Scattering From A Tenuous Random Medium, Jonathan Blackledge
Imaging Reconstruction For Light Scattering From A Tenuous Random Medium, Jonathan Blackledge
Conference papers
We consider the basis for describing strong scattering in terms of diffusive processes based on the diffusion equation. Intermediate strength scattering is then considered in terms of a fractional diffusion equation which is studied using results from fractional calculus. This approach is justified in terms of the generalization of a random walk model with no statistical bias in the phase to a random walk that has a phase bias and is thus, only `partially' or `fractionally' diffusive. A Green's function solution to the fractional diffusion equation is studied and a result derived that provides a model for an incoherent image …