Name
Abstract | ||
|---|---|---|
Over the past few years, hyperspectral data exploitation aimed at detecting spectral anomalies within remotely sensed images has been of growing interest in many applications. In this letter, we are interested in an anomaly detection (AD) scheme for hyperspectral images in which spectral anomalies are defined with respect to a statistical model of the background probability density function (PDF).... |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/LGRS.2010.2099103 | IEEE Geoscience and Remote Sensing Letters |
Keywords | Field | DocType |
Bandwidth,Hyperspectral imaging,Pixel,Estimation,Kernel,Bayesian methods | Anomaly detection,Likelihood-ratio test,Pattern recognition,Hyperspectral imaging,Nonparametric statistics,Probability distribution,Smoothing,Artificial intelligence,Statistical model,Mathematics,Estimator | Journal |
Volume | Issue | ISSN |
8 | 4 | 1545-598X |
Citations | PageRank | References |
7 | 0.47 | 3 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tiziana Veracini | 1 | 39 | 3.61 |
| Stefania Matteoli | 2 | 152 | 18.05 |
| Marco Diani | 3 | 261 | 30.99 |
| Giovanni Corsini | 4 | 299 | 40.26 |