Name
Title | ||
|---|---|---|
A Statistical Approach for Automatic Detection of Ocean Disturbance Features From SAR Images |
Abstract | ||
|---|---|---|
Extraction of features from images has been a goal of researchers since the early days of remote sensing. This paper presents a statistical approach to detect dark curvilinear features due to ocean disturbances caused by wind, movements of surface or underwater objects, and oil spill from SAR images. The image is first enhanced to emphasize the dark curvilinear features using a statistical approac... |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/JSTARS.2012.2186630 | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Keywords | Field | DocType |
Image segmentation,Feature extraction,Sea surface,Noise,Remote sensing,Surface waves | Graph theory,Computer vision,Iterative method,Segmentation,Remote sensing,Image segmentation,Feature extraction,Curvilinear coordinates,Artificial intelligence,Gaussian noise,Mathematics,Underwater | Journal |
Volume | Issue | ISSN |
5 | 4 | 1939-1404 |
Citations | PageRank | References |
7 | 0.69 | 13 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| D. Chaudhuri | 1 | 167 | 16.32 |
| A Samal | 2 | 1033 | 213.54 |
| amit agrawal | 3 | 7 | 0.69 |
| sanjay | 4 | 7 | 0.69 |
| A. Mishra | 5 | 34 | 5.00 |
| v gohri | 6 | 7 | 0.69 |
| ramesh c agarwal | 7 | 14 | 1.28 |