Alteration Detection of Multispectral/Hyperspectral Images Using Dual-Path Partial Recurrent Networks

Alteration Detection of Multispectral/Hyperspectral Images Using Dual-Path Partial Recurrent Networks

Numerous alteration detection methods are designed based on image transformation algorithms and divergence of bi-temporal images. In the process of feature transformation, pseudo variant information caused by complex external factors will be highlighted. As a result, the error of divergence between...

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Bibliographic Details
Main Authors: Jinlong Li, Xiaochen Yuan, Li Feng
Format: Article
Language:English
Published: MDPI AG 2021-11-01
Series:Remote Sensing
Subjects:
Unsupervised Slow Feature Analysis (USFA)
Dual-path Partial Recurrent Networks (D-PRNs)
Iteratively Reweighted Multivariate Alteration Detection (IRMAD)
Principal Component Analysis (PCA)
Online Access:https://www.mdpi.com/2072-4292/13/23/4802

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https://www.mdpi.com/2072-4292/13/23/4802

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