Name
Title | ||
|---|---|---|
Fast Real-Time Causal Linewise Progressive Hyperspectral Anomaly Detection via Cholesky Decomposition. |
Abstract | ||
|---|---|---|
Real-time processing of anomaly detection has become one of the most important issues in hyperspectral remote sensing. Due to the fact that most widely used hyperspectral imaging spectrometers work in a pushbroom fashion, it is necessary to process the incoming data line in a causal linewise progressive manner with no future data involved. In this study, we proposed several processes to well impro... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/JSTARS.2017.2725382 | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Keywords | Field | DocType |
Real-time systems,Hyperspectral imaging,Detectors,Correlation,Covariance matrices,Earth | Anomaly detection,Computer vision,Linear system,Matrix (mathematics),Floating point,Computer science,Positive-definite matrix,Hyperspectral imaging,Artificial intelligence,Computational complexity theory,Cholesky decomposition | Journal |
Volume | Issue | ISSN |
10 | 10 | 1939-1404 |
Citations | PageRank | References |
3 | 0.40 | 18 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lifu Zhang | 1 | 87 | 28.77 |
| Bo Peng | 2 | 19 | 6.08 |
| Feizhou Zhang | 3 | 21 | 4.89 |
| Lizhe Wang | 4 | 2973 | 191.46 |
| Hongming Zhang | 5 | 10 | 2.54 |
| Peng Zhang | 6 | 27 | 7.09 |
| Qingxi Tong | 7 | 15 | 3.36 |