Name
Title | ||
|---|---|---|
Multi-Temporal Approach To Atmospheric Effects Compensation In Hyperspectral Image Classification |
Abstract | ||
|---|---|---|
This paper presents a multi-temporal approach to compensate the atmospheric effects in spaceborne hyperspectral images. It focuses on applications where a hyperspectral sensor periodically acquires images of the same scene and such images have to be classified. The method assumes that a reference reflectance image of the region of interest, equipped with an accurate classification map, is available. Such an image and the corresponding classification map represent the database that will be a reference for the classification of temporally subsequent images over the same scene. The multi-temporal approach allows the classification to be performed on at sensor radiance data and it does not require the knowledge of the atmospheric conditions at the acquisition time. |
Year | Venue | Keywords |
|---|---|---|
2015 | 2015 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | Radiometric equalization, multi-temporal classification |
Field | DocType | ISSN |
Computer vision,Full spectral imaging,Computer science,Remote sensing,Feature extraction,Hyperspectral imaging,Radiometry,Artificial intelligence,Region of interest,Statistical classification,Reflectivity,Radiance | Conference | 2153-6996 |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nicola Acito | 1 | 191 | 22.58 |
| Marco Diani | 2 | 261 | 30.99 |
| Stefania Matteoli | 3 | 152 | 18.05 |
| Giovanni Corsini | 4 | 299 | 40.26 |