Hyperspectral anomaly detection with self-supervised anomaly prior.

• Tác giả: Leyuan Fang, Kai Jiang, Yunsong Li, Yidan Liu, Weiying Xie, Jiaqing Zhang
• Ngôn ngữ: eng
• Thông tin xuất bản: United States : Neural networks : the official journal of the International Neural Network Society , 2025
• Bộ sưu tập: NCBI
• ID: 733711

Tóm tắt

Hyperspectral anomaly detection (HAD) can identify and locate the targets without any known information and is widely applied in Earth observation and military fields. The majority of existing HAD methods use the low-rank representation (LRR) model to separate the background and anomaly through mathematical optimization, in which the anomaly is optimized with a handcrafted sparse prior (e.g., ℓ