Name
Title | ||
|---|---|---|
Class-Specific Random Forest With Cross-Correlation Constraints for Spectral-Spatial Hyperspectral Image Classification. |
Abstract | ||
|---|---|---|
A class-specific random forest (RF) model with cross-correlation constraints is developed for the spectral-spatial hyperspectral image (HSI) classification. The novelties of this letter are as follows: 1) normalization of the spectral feature vector by using cross correlation in the stochastic process and proposal of a spectral-spatial hybrid feature extraction based on the cross-correlation analy... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/LGRS.2016.2637561 | IEEE Geoscience and Remote Sensing Letters |
Keywords | Field | DocType |
Radio frequency,Feature extraction,Training,Vegetation,Correlation,Support vector machines,Hyperspectral sensors | Hyperspectral image classification,Cross-correlation,Computer vision,Pattern recognition,Artificial intelligence,Random forest,Mathematics | Journal |
Volume | Issue | ISSN |
14 | 2 | 1545-598X |
Citations | PageRank | References |
4 | 0.38 | 9 |
Authors | ||
5 | ||