An Efficient Feature Extraction Network for Unsupervised Hyperspectral Change Detection

An Efficient Feature Extraction Network for Unsupervised Hyperspectral Change Detection

Change detection (CD) in hyperspectral images has become a research hotspot in the field of remote sensing due to the extremely wide spectral range of hyperspectral images compared to traditional remote sensing images. It is challenging to effectively extract features from redundant high-dimensional...

Full description

Bibliographic Details
Main Authors: Hongyu Zhao, Kaiyuan Feng, Yue Wu, Maoguo Gong
Format: Article
Language:English
Published: MDPI AG 2022-09-01
Series:Remote Sensing
Subjects:
change detection (CD)
recurrent neural network (RNN)
convolutional neural network (CNN)
hyperspectral image (HSI)
Online Access:https://www.mdpi.com/2072-4292/14/18/4646

Internet

https://www.mdpi.com/2072-4292/14/18/4646

Similar Items