Abstract

Advancements in hyperspectral imaging systems, data processing, and collection methods, have allowed for comprehensive spectral assessment of terrestrial objects to assist in a vast array of imaging problems previously deemed too complex. As the field evolves and more research is completed, the boundaries of what is capable are constantly pushed to new thresholds. At this junction, there exists an opportunity for the capabilities of these new creations to exceed our ability to prove their efficiency and efficacy. One area where this is true, is in the assessment of new hyperspectral panchromatic sharpening (HPS) algorithms. This is due to the lack of a true multi-resolution hyperspectral data focused on the same scene, which is needed to properly test these algorithms. Typically, the assessment process awaiting a HPS algorithm starts by taking a high-resolution Hyperspectral Image (HSI), which is then spatially degraded so that after the sharpening process, the result can be compared to the original and analyzed for accuracy. Presentations featuring the results of such algorithms often lead to immediate questions about quantitative assessments based solely on simulated low-resolution data. To address this problem, a collection experiment seeking to create a multi-resolution hyperspectral data set was designed and completed in Henrietta, NY on July 24th, 2020. Imagery of 48 felt targets, ranging in size from 5 cm to 30 cm and in six different colors, was collected in three resolutions by the Rochester Institute of Technology (RIT) MX-1 sUAS imaging system. In addition to a high resolution 5-band frame camera, the MX-1 utilizes a 272-band hyperspectral line imager that features a silicon detector, 1.88cm GSD at 30m flight altitude, and is responsive from approximately 400nm to 1000nm. To create the desired multi-resolution imagery, three flights were performed, and images of the target scene were collected at flight heights of 30m, 60m, and 120m. The resulting imagery possesses ratios of 2:1 and 4:1 spatial resolution relative to the lowest altitude flight. Use of this data in the evaluation process of HPS algorithms ensures that the radiometric accuracy of the result and the effectiveness of the sharpening method employed can be better ascertained through quantitative analysis of the inputs and output after being applied to this non-simulated multiresolution hyperspectral data set. During planning and after collection, care was taken to rigorously document the data set, its structure, and features, as the intention exists for the data to be used for various purposes long exceeding the extent of its immediate usefulness to researchers at RIT. Additional documentation provided as ancillary metadata describes the spectral signatures of all non-environmental materials present in the HSI target scene, the process of creating both the targets and their layout, as well as the collection plan, the data itself, post processing steps, and preliminary experiments undertaken to improve end-user understanding and ease of use. This documentation also includes an assessment surmised through understanding the flaws present within the data, and portions of the collection plan which did not lead to the intended outcome. Because of the efforts described in this document, there now exists a multi-resolution hyperspectral data set of a known target scene with highly documented ground truth. This data and report will prove useful in the assessment of HPS algorithms currently under development, but also has the potential to assist as useful test data for various applications within the fields of hyperspectral imaging and remote sensing.

Library of Congress Subject Headings

Hyperspectral imaging--Evaluation; Remote sensing--Data processing

Publication Date

12-2-2021

Document Type

Thesis

Student Type

Graduate

Degree Name

Imaging Science (MS)

Department, Program, or Center

Chester F. Carlson Center for Imaging Science (COS)

Advisor

David Messinger

Advisor/Committee Member

John Kerekes

Advisor/Committee Member

Emmett J. Ientilucci

Campus

RIT – Main Campus

Plan Codes

IMGS-MS

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