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A Study On The Impact Of Nonlinear Effects On Hyperspectral Sub-Pixel Target Detection, Colin J. Maloney

Theses

In the realm of hyperspectral (HS) sub-pixel target detection, the Linear Mixing Model (LMM) proposes that the macroscopic interaction between incident light and materials in a scene may be modeled as linear. For individual pixels in hyperspectral data which contain multiple materials, this means that they may be accurately represented by a linear combination of the spectra of those pure materials, which are often called endmembers. However, when nonlinear mixing, such as shadowing and adjacent reflections, are present, the foundational assumptions of the LMM are violated and its accuracy in predicting target detection performance is reduced. This thesis aims to …

Hyperspectral Properties Of Date Palm Trees (Phoenix Dactylifera L.), Mohamed Ali Saeed Ahmed Al Abdouli

Theses

The goal of this study is to classify the Date Palm varieties based on hyperspectral signature technology since it is difficult to identify the Date Palm cultivars without fruits. It will also help to obtain the hyperspectral signature for different types of date palm trees. Moreover, it also assists to determine the wavelength fingerprint of each cultivar and to recommend the best classification protocol differentiating among different cultivars based on spectral signature. Utilizing the Hyperspectral imaging technology precisely on the leaves of different Date Palm cultivars, thus facilitating identification of date palm cultivars without the fruits and make the spatial …

A Hyperspectral Image Classification Approach To Pigment Mapping Of Historical Artifacts Using Deep Learning Methods, Di Bai

Theses

Hyperspectral image (HSI) classification has been used to identify material diversity in remote sensing images. Recently, hyperspectral imaging has been applied to historical artifact studies. For example, the Gough Map, one of the earliest surviving maps of Britain, was imaged in 2015 using a hyperspectral imaging system while in the collection at the Bodleian Library, Oxford University. The collection of the HSI data was aimed at pigment analysis for the material diversity of its composition and potentially the timeline of its creation. Traditional methods used spectral unmixing and the spectral angle mapper to classify features in HSIs of historical artifact, …

Machine Learning For Robust Understanding Of Scene Materials In Hyperspectral Images, Utsav B. Gewali

Theses

The major challenges in hyperspectral (HS) imaging and data analysis are expensive sensors, high dimensionality of the signal, limited ground truth, and spectral variability. This dissertation develops and analyzes machine learning based methods to address these problems. In the first part, we examine one of the most important HS data analysis tasks-vegetation parameter estimation. We present two Gaussian processes based approaches for improving the accuracy of vegetation parameter retrieval when ground truth is limited and/or spectral variability is high. The first is the adoption of covariance functions based on well-established metrics, such as, spectral angle and spectral correlation, which are …

Combining Hyperspectral Imaging And Small Unmanned Aerial Systems For Grapevine Moisture Stress Assessment, Rinaldo R. Izzo

Theses

It has been shown that mild water deficit in grapevine contributes to wine quality, in terms of especially grape and subsequent wine flavor. Water deficit irrigation and selective harvesting are implemented to optimize quality, but these approaches require rigorous measurement of vine water status. While traditional in-field physiological measurements have made operational implementation onerous, modern small unmanned aerial systems (sUAS) have presented the unique opportunity for rigorous management across vast areas. This study sought to fuse hyperspectral remote sensing, sUAS, and sound multivariate analysis techniques for the purposes of assessing grapevine water status. High-spatial and -spectral resolution hyperspectral data were …

Hyperspectral Imaging Evaluation Of The Freshness Of Mushrooms (Agaricus Bisporus), Meera Hmoud Saeed Aldhaheri

Theses

Hyperspectral imaging (HSI) is a non-destructive analytical tool that can be used for sensing multiple attributes of foods. This thesis evaluates the application of HSI for measuring the freshness of the mushroom Agaricus bisporus (A. bisporus) in comparison with traditional seed methods. Three separate experiments were performed with 135 mushroom samples stored either in packed or unpacked conditions for 11 days. The overall results suggest that the HSI spectral region between 400 and 1000 nm is suitable for the inspection of mushroom freshness. Two distinguishing variables that aligned with physicochemical and microbiological analysis were recognized. Moisture loss was the main …

Hyperspectral Imaging System Model Implementation And Analysis, Bo Ding

Theses

In support of hyperspectral imaging system design and parameter trade-off research, an analytical end-to-end model to simulate the remote sensing system pipeline and to forecast remote sensing system performance has been implemented. It is also being made available to the remote sensing community through a website. Users are able to forecast hyperspectral imaging system performance by defining an observational scenario along with imaging system parameters.

For system modeling, the implemented analytical model includes scene, sensor and target characteristics as well as atmospheric features, background spectral reflectance statistics, sensor specifications and target class reflectance statistics. The sensor model has been extended …

Analysis Of Compressive Sensing For Hyperspectral Remote Sensing Applications, Maria Busuioceanu

Theses

Compressive Sensing (CS) systems capture data with fewer measurements than traditional sensors assuming that imagery is redundant and compressible in the spectral and spatial dimensions. This thesis utilizes a model of the Coded Aperture Snapshot Spectral Imager-Dual Disperser (CASSI-DD) to simulate CS measurements from traditionally sensed HyMap images. A novel reconstruction algorithm that combines spectral smoothing and spatial total variation (TV) is used to create high resolution hyperspectral imagery from the simulated CS measurements. This research examines the effect of the number of measurements, which corresponds to the percentage of physical data sampled, on the quality of simulated CS data …

Hyperspectral Imaging And Association Phenomenology Of Pedestrians In A Cluttered Urban Environment, Jared Herweg

Theses

Remote hyperspectral imaging (HSI) has shown promise in several applications such as object detection and tracking. Typically research has focused on large objects, such as vehicles, for tracking due to the spatial resolution of current operational HSI systems. This research seeks to extend the utility of applying HSI to human pedestrian detection using the reflective solar spectral range between 400 - 2500 nm. A phenomenological investigation of a novel scheme to differentiate between pedestrians is studied. By applying the basics of detection theory, this research focuses on being able to differentiate between pedestrians, as well as background materials. Specifically, this …