Name
Title | ||
|---|---|---|
Assessment Of The Relevance Of Information Derived From The Unmixing Of Polarimetric Radar Images |
Abstract | ||
|---|---|---|
A new method to unmix radar polarimetric images with optical images was proposed. This method has pointed out that the unmixing model is able to split off polarimetric information on a land cover type basis. In this paper unmixed radar polarimetric images obtained are compared with the observed ones in non-mixed conditions. Then, Cloude and Pottier decomposition is performed on the unmixed and observed radar images to asses whether the understanding of physical scattering mechanisms is improved with the unmixing. Finally, a classification experiment is designed to determine whether this fusion framework make the transfer of information from the optical images to the unmixed radar images possible. |
Year | Venue | Keywords |
|---|---|---|
2015 | 2015 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | unmixing, radar polarimetry, polarimetric decomposition |
Field | DocType | ISSN |
Radar,Computer vision,Radar imaging,Polarimetry,Computer science,Remote sensing,Lidar,Artificial intelligence,Scattering,Land cover,Optical imaging,Light scattering | Conference | 2153-6996 |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sebastien Giordano | 1 | 1 | 1.45 |
| Grégoire Mercier | 2 | 605 | 52.49 |
| Jean-Paul Rudant | 3 | 90 | 12.90 |