Enhancing Binary Change Detection in Hyperspectral Images Using an Efficient Dimensionality Reduction Technique Within Adversarial Learning

Enhancing Binary Change Detection in Hyperspectral Images Using an Efficient Dimensionality Reduction Technique Within Adversarial Learning

Detecting binary changes in co-registered bitemporal hyperspectral images (HSIs) using deep learning methods is challenging due to the high dimensionality of spectral data and significant variations between images. To address this challenge, previous approaches often used dimensionality reduction me...

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Bibliographic Details
Main Authors: Amel Oubara, Falin Wu, Guoxin Qu, Reza Maleki, Gongliu Yang
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Remote Sensing
Subjects:
hyperspectral bitemporal images
dimensionality reduction
binary change detection
adversarial networks
autoencoder
Online Access:https://www.mdpi.com/2072-4292/17/1/5
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