Name
Title | ||
|---|---|---|
Performance of Kriging-Based Soft Classification on WiFS/IRS-1D Image Using Ground Hyperspectral Signatures |
Abstract | ||
|---|---|---|
Hard/soft classification techniques are the conventional ways of image classification on satellite data. These classifiers have a number of drawbacks. First, these approaches are inappropriate for mixed pixels. Second, these approaches do not consider spatial variability. Kriging-based soft classification (KBSC) is a nonparametric geostatistical method. It exploits the spatial variability of the c... |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/LGRS.2009.2016988 | IEEE Geoscience and Remote Sensing Letters |
Keywords | Field | DocType |
Hyperspectral imaging,Hyperspectral sensors,Satellites,Discrete wavelet transforms,Image classification,Maximum likelihood estimation,Remote sensing,Spectroradiometers,Object detection,Gaussian distribution | Remote sensing,Radiometry,Spatial variability,Artificial intelligence,Subpixel rendering,Contextual image classification,Kriging,Computer vision,Object detection,Pattern recognition,Hyperspectral imaging,Pixel,Mathematics | Journal |
Volume | Issue | ISSN |
6 | 3 | 1545-598X |
Citations | PageRank | References |
3 | 0.45 | 6 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sumanta K. Das | 1 | 3 | 0.45 |
| Randhir Singh | 2 | 16 | 4.57 |