Name
Abstract | ||
|---|---|---|
We present a new framework, called multisensor coupled spectral unmixing (MuCSUn), that solves unmixing problems involving a set of multisensor time-series spectral images in order to understand dynamic changes of the surface at a subpixel scale. The proposed methodology couples multiple unmixing problems based on regularization on graphs between the time-series data to obtain robust and stable un... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TGRS.2017.2655115 | IEEE Transactions on Geoscience and Remote Sensing |
Keywords | Field | DocType |
Satellites,Robustness,Earth,Remote sensing,Optimization,Atmospheric modeling,Mixture models | Atmospheric correction,Computer vision,Time series,Normalization (statistics),Remote sensing,Robustness (computer science),Preprocessor,Synthetic data,Artificial intelligence,Subpixel rendering,Mathematics,Mixture model | Journal |
Volume | Issue | ISSN |
55 | 5 | 0196-2892 |
Citations | PageRank | References |
3 | 0.39 | 33 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Naoto Yokoya | 1 | 439 | 36.36 |
| Xiao Xiang Zhu | 2 | 896 | 103.00 |
| Antonio Plaza | 3 | 3475 | 262.63 |