Name
Abstract | ||
|---|---|---|
Hyperspectral-based change detection is often inadvertently affected by image artifacts, reducing the accuracy of the change detector. We present a Hyperspectral Change Detection (HSCD) process to distinguish parallax-induced change from legitimate change. Image parallax decreases the accuracy of change detection results. The approach introduced in this paper utilizes a combination of a spectral change detector and stereo geometry to reduce parallax-induced false alarms. Image parallax is determined by considering the error in the epipolar constraint, meaning the corresponding points between two images must lie on epipolar lines. Experimental analysis shows a false alarm reduction by nearly one order of magnitude on synthetic hyperspectral imagery and nearly two orders of magnitude on real hyperspectral imagery. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/IGARSS.2012.6350982 | Geoscience and Remote Sensing Symposium |
Keywords | Field | DocType |
computational geometry,geophysical image processing,stereo image processing,HSCD,epipolar constraint,hyperspectral change detection,hyperspectral imagery,image artifacts,image parallax,legitimate change,parallax-induced changes,parallax-induced false alarms,stereo geometry,Change detection,hyperspectral images | Computer vision,False alarm,Change detection,Epipolar geometry,Parallax,Computer science,Computational geometry,Remote sensing,Hyperspectral imaging,Artificial intelligence,Order of magnitude,Detector | Conference |
ISSN | ISBN | Citations |
2153-6996 E-ISBN : 978-1-4673-1158-8 | 978-1-4673-1158-8 | 1 |
PageRank | References | Authors |
0.38 | 5 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Karmon Vongsy | 1 | 6 | 1.59 |
| Michael J. Mendenhall | 2 | 51 | 7.58 |
| Michael T. Eismann | 3 | 326 | 19.71 |
| Gilbert L. Peterson | 4 | 251 | 38.75 |