Unified Dynamic Dictionary and Projection Optimization With Full-Rank Representation for Hyperspectral Anomaly Detection
Hyperspectral anomaly detection (HAD) aims to classify each pixel in a hyperspectral image as either background or anomaly without requiring labeled data. Traditional reconstruction based methods model the background using a predefined static background dictionary and low-rank representation coeffic...
Saved in:
Main Authors: | Hongran Li, Chao Wei, Yizhou Yang, Zhaoman Zhong, Ming Xu, Dongqing Yuan |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
|
Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10815627/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Hyperspectral Anomaly Detection Based on Intrinsic Image Decomposition and Background Subtraction
by: Jiao Jiao, et al.
Published: (2025-01-01) -
<inline-formula><tex-math notation="LaTeX">$\mathrm{D}^{3}$</tex-math></inline-formula>T: Deep Denoising Dictionary Tensor for Hyperspectral Anomaly Detection
by: Qiangqiang Shen, et al.
Published: (2025-01-01) -
A Tensor-Based Go Decomposition Method for Hyperspectral Anomaly Detection
by: Meiping Song, et al.
Published: (2025-01-01) -
A novel graph convolution and frequency domain filtering approach for hyperspectral anomaly detection
by: Yang Ding, et al.
Published: (2025-01-01) -
Coloration in a Praying Mantis: Color Change, Sexual Color Dimorphism, and Possible Camouflage Strategies
by: Leah Y. Rosenheim, et al.
Published: (2025-01-01)