Laser & Optoelectronics Progress, Volume. 59, Issue 12, 1228003(2022)
Graph Regularized Low-Rank and Collaborative Representation for Hyperspectral Anomaly Detection
The aim of hyperspectral anomaly detection is to find targets that are spectrally distinct from their surrounding background pixels. Many algorithms for hyperspectral anomaly detection have been proposed by researchers. Among these, the low-rank and collaborative representation detector (LRCRD) can not only analyze the hyperspectral correlation between all pixels but also constrain the coefficient matrix of the dictionary using low-rank and
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Qi Wu, Yanguo Fan, Bowen Fan, Dingfeng Yu. Graph Regularized Low-Rank and Collaborative Representation for Hyperspectral Anomaly Detection[J]. Laser & Optoelectronics Progress, 2022, 59(12): 1228003
Category: Remote Sensing and Sensors
Received: Mar. 25, 2021
Accepted: Jun. 10, 2021
Published Online: Jun. 6, 2022
The Author Email: Wu Qi (wqzwy0825@163.com)