UNet-Based End-to-End Anomaly Detection With Computational Hyperspectral Imaging

UNet-Based End-to-End Anomaly Detection With Computational Hyperspectral Imaging

Most existing hyperspectral anomaly detection methods are developed and validated on numerical datasets, focusing on simulations rather than practical applications. To bridge this gap, we introduce an anomaly detection system that directly utilizes the encoded light intensities (ELIs), avoiding the...

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Bibliographic Details
Main Authors: Weiming Shi, Junren Wen, Yipeng Chen, Yu Shao, Haiqi Gao, Xuehui Wang, Chenying Yang
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Computational hyperspectral imaging
cost matrix
encoded light intensities (ELIs)
end-to-end
UNet
Online Access:https://ieeexplore.ieee.org/document/10988569/
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