JointNet: Multitask Learning Framework for Denoising and Detecting Anomalies in Hyperspectral Remote Sensing

JointNet: Multitask Learning Framework for Denoising and Detecting Anomalies in Hyperspectral Remote Sensing

One of the significant challenges with traditional single-task learning-based anomaly detection using noisy hyperspectral images (HSIs) is the loss of anomaly targets during denoising, especially when the noise and anomaly targets are similar. This issue significantly affects the detection accuracy....

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Bibliographic Details
Main Authors: Yingzhao Shao, Shuhan Li, Pengfei Yang, Fei Cheng, Yueli Ding, Jianguo Sun
Format: Article
Language:English
Published: MDPI AG 2024-07-01
Series:Remote Sensing
Subjects:
hyperspectral image (HSI)
anomaly detection
denoising
autoencoder (AE)
multitask learning
minimum noise fraction rotation (MNF)
Online Access:https://www.mdpi.com/2072-4292/16/14/2619

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https://www.mdpi.com/2072-4292/16/14/2619

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