<inline-formula><tex-math notation="LaTeX">$\mathrm{D}^{3}$</tex-math></inline-formula>T: Deep Denoising Dictionary Tensor for Hyperspectral Anomaly Detection

<inline-formula><tex-math notation="LaTeX">$\mathrm{D}^{3}$</tex-math></inline-formula>T: Deep Denoising Dictionary Tensor for Hyperspectral Anomaly Detection

Hyperspectral anomaly detection (HAD) approaches with tensor low-rank representation (TLRR) have shown engaging performance, which are capable of capturing abundant spectral and spatial information and, hence, extracting sparse anomalies from the low-rank background without ruining the intrinsic geo...

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Bibliographic Details
Main Authors: Qiangqiang Shen, Zonglin Liu, Hanzhang Wang, Yanhui Xu, Yongyong Chen, Yongsheng Liang
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Deep denoising
hyperspectral anomaly detection (HAD)
low-rank representation (LRR)
low-rank tensor
Online Access:https://ieeexplore.ieee.org/document/10818590/
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https://ieeexplore.ieee.org/document/10818590/

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