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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الحاوية / القاعدة:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
المؤلفون الرئيسيون:	Hongran Li, Chao Wei, Yizhou Yang, Zhaoman Zhong, Ming Xu, Dongqing Yuan
التنسيق:	مقال
اللغة:	الإنجليزية
منشور في:	IEEE 2025-01-01
الموضوعات:	Background dictionary background representation (BR) hyperspectral anomaly detection (HAD) nonnegative full-rank constraint (NFRC) projection operator
الوصول للمادة أونلاين:	https://ieeexplore.ieee.org/document/10815627/