SSA-LHCD: A Singular Spectrum Analysis-Driven Lightweight Network with 2-D Self-Attention for Hyperspectral Change Detection

As an emerging research hotspot in contemporary remote sensing, hyperspectral change detection (HCD) has attracted increasing attention in remote sensing Earth observation, covering land mapping changes and anomaly detection. This is primarily attributable to the unique capacity of hyperspectral ima...

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Bibliographic Details

Published in:	Remote Sensing
Main Authors:	Yinhe Li, Jinchang Ren, Yijun Yan, Genyun Sun, Ping Ma
Format:	Article
Language:	English
Published:	MDPI AG 2024-06-01
Subjects:	hyperspectral imagery (HSI) hyperspectral change detection (HCD) deep learning singular spectral analysis (SSA) residual block
Online Access:	https://www.mdpi.com/2072-4292/16/13/2353