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...
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Main Authors: | , , , , , |
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Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
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Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10815627/ |
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