Name
Abstract | ||
|---|---|---|
Anomaly detection is one of the practical applications in hyperspectral imagery (HSI) over the last two decades. In this paper, we propose a combined similarity criterion anomaly detector (CSCAD) method for HSI anomaly detection. The proposed method approximates the background using the surrounding neighbor pixels. Then, the residual error is obtained by subtracting the approximated background fro... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/JSTARS.2018.2870123 | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Keywords | Field | DocType |
Hyperspectral imaging,Anomaly detection,Detectors,Kernel,Object detection,Contamination | Kernel (linear algebra),Anomaly detection,Residual,Object detection,Computer vision,Pattern recognition,Outlier,Hyperspectral imaging,Artificial intelligence,Pixel,Detector,Mathematics | Journal |
Volume | Issue | ISSN |
11 | 11 | 1939-1404 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maryam Vafadar | 1 | 0 | 0.34 |
| Hassan Ghassemian | 2 | 396 | 34.04 |