Unsupervised Detection in Hyperspectral Imagery

Thomas Bahr; David Streutker; Greg Terrie; Michael Ingram

doi:10.1364/HMISE.2023.HW5C.3

Optica Sensing Congress 2023 (AIS, FTS, HISE, Sensors, ES)
Technical Digest Series (Optica Publishing Group, 2023),
paper HW5C.3
•https://doi.org/10.1364/HMISE.2023.HW5C.3

Unsupervised Detection in Hyperspectral Imagery

Thomas Bahr, David Streutker, Greg Terrie, and Michael Ingram

Hyperspectral/Multispectral Imaging and Sounding of the Environment 2023

Munich Germany
30 July–3 August 2023
ISBN: 978-1-957171-24-1

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Image Processing, Algorithm Development, and Machine Learning (HW5C)

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T. Bahr, D. Streutker, G. Terrie, and M. Ingram, "Unsupervised Detection in Hyperspectral Imagery," in Optica Sensing Congress 2023 (AIS, FTS, HISE, Sensors, ES), Technical Digest Series (Optica Publishing Group, 2023), paper HW5C.3.

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Abstract

Performance of six state-of-the-art unsupervised target detection algorithms were compared, including three least squares spectral unmixing based methods. UnConstrained Abundance, Nonnegatively Constrained Abundance and Fully Constrained Abundance performed best at detecting the desired endmembers.

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