Name
Abstract | ||
|---|---|---|
Aerial and satellite images are projected images where clouds and cloud-shadows cause interferences in them. Detecting the presence of clouds over a region is important to isolate cloud-free pixels used to retrieve atmospheric thermodynamic information and surface geophysical parameters. This paper describes an adaptive algorithm to reduce both effects of clouds and their shadows from remote sensed images. The proposed method is implemented and tested with remote sensed RGB and monochrome images and also for visible (VIS) satellite imagery and infrared (IR) imagery. The results show that this approach is effective in extracting infected pixels and their compensation. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-32063-7_36 | INTELLIGENT INFORMATICS |
Keywords | Field | DocType |
Adaptive segmentation,Average local luminance,Shadowing effect | Satellite,Satellite imagery,Computer science,Monochrome,Remote sensing,Pixel,RGB color model,Adaptive algorithm,Infrared,Cloud computing | Conference |
Volume | ISSN | Citations |
182 | 2194-5357 | 0 |
PageRank | References | Authors |
0.34 | 2 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lizy Abraham | 1 | 0 | 0.68 |
| M. Sasikumar | 2 | 0 | 0.68 |