Name
Title | ||
|---|---|---|
Supervised Polarimetric SAR Image Classification Using Tensor Local Discriminant Embedding. |
Abstract | ||
|---|---|---|
Feature extraction is a very important step for polarimetric synthetic aperture radar (PolSAR) image classification. Many dimensionality reduction (DR) methods have been employed to extract features for supervised PolSAR image classification. However, these DR-based feature extraction methods only consider each single pixel independently and thus fail to take into account the spatial relationship ... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TIP.2018.2815759 | IEEE Transactions on Image Processing |
Keywords | Field | DocType |
Tensile stress,Feature extraction,Dimensionality reduction,Covariance matrices,Support vector machines,Speckle,Matrix decomposition | Spatial analysis,Computer vision,Data set,Dimensionality reduction,Pattern recognition,Support vector machine,Feature extraction,Pixel,Artificial intelligence,Speckle noise,Contextual image classification,Mathematics | Journal |
Volume | Issue | ISSN |
27 | 6 | 1057-7149 |
Citations | PageRank | References |
4 | 0.43 | 12 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiayuan Huang | 1 | 24 | 4.47 |
| Hong Qiao | 2 | 1147 | 110.95 |
| Bo Zhang | 3 | 253 | 21.61 |
| Xiangli Nie | 4 | 40 | 5.76 |