Name
Abstract | ||
|---|---|---|
A compressive sensing framework is described for hyperspectral imaging. It is based on the widely used linear mixing model, LMM, which represents hyperspectral pixels as convex combinations of small numbers of endmember (material) spectra. The coefficients of the endmembers for each pixel are called proportions. The endmembers and proportions are often the sought-after quantities; the full image i... |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/LGRS.2011.2167652 | IEEE Geoscience and Remote Sensing Letters |
Keywords | Field | DocType |
Hyperspectral imaging,Sensors,Materials,Noise,Compressed sensing,Image coding | Endmember,Remote sensing,Artificial intelligence,Intermediate language,Compressed sensing,Iterative reconstruction,Computer vision,Pattern recognition,Image coding,Hyperspectral imaging,Regular polygon,Pixel,Mathematics | Journal |
Volume | Issue | ISSN |
9 | 3 | 1545-598X |
Citations | PageRank | References |
5 | 0.43 | 9 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alina Zare | 1 | 297 | 32.19 |
| Paul Gader | 2 | 1909 | 196.70 |
| karthik s gurumoorthy | 3 | 52 | 10.09 |