Name
Title | ||
|---|---|---|
Mineral Absorption Feature Extraction From High-Density Vegetation Area Using Reference Spectral Background Removal. |
Abstract | ||
|---|---|---|
Hyperspectral remote sensing has been verified to be an effective tool in mineral information extraction. The existence of vegetation can cause a major problem for mineral exploration, and diagnostic absorption feature has the potential to be the key factor in mineral information extraction from a vegetation-covered area. This letter presents a new approach of mineral absorption feature extraction... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/LGRS.2016.2620174 | IEEE Geoscience and Remote Sensing Letters |
Keywords | Field | DocType |
Vegetation mapping,Minerals,Feature extraction,Absorption,Data models,Hyperspectral sensors | Data modeling,Vegetation,Remote sensing,High density,Feature extraction,Hyperspectral imaging,Information extraction,Mineral exploration,Mathematics,Mineral absorption | Journal |
Volume | Issue | ISSN |
13 | 12 | 1545-598X |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hengqian Zhao | 1 | 0 | 0.34 |
| Xuesheng Zhao | 2 | 3 | 2.54 |
| Lifu Zhang | 3 | 87 | 28.77 |
| Keming Yang | 4 | 0 | 1.35 |
| Hao Sun | 5 | 0 | 0.34 |