Name
Abstract | ||
|---|---|---|
Hyperion images are currently processed to level 1a (from level 0 or raw data). These level 1a images are files of radiometrically corrected data in units of either watts/(sr × micron × m2) × 40 for VNIR bands or watts/(sr × micron × m2) × 80 for SWIR bands. Each distributed Hyperion level 1a im- age tape contains a log file, called "(EO-1 identifier).fix.log", that reports the bad or corrupted pixels (called known bad pixels) found during the pre-flight checking, and details how they were fixed. All bad pixels should be corrected in a level 1a image. However, bad pixels are still evident. In addition, there are dark vertical stripes in the image that are not reported in the log file. In this paper, we introduce a method to detect and correct the bad pixels and vertical stripes (we will refer to these occurrences as abnormal pixels). Images from the Greater Victoria Watershed and other EVEOSD test sites are used to determine how stationary the locations of the abnormal pixels are. After abnormal pixel correction a Hyperion image is ready for geometric correction, atmospheric correction, and further analysis. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1109/IGARSS.2002.1026105 | IGARSS |
Keywords | Field | DocType |
error correction,error correction codes,geophysical signal processing,geophysical techniques,image enhancement,image processing,terrain mapping,Hyperion,IR,SWIR,VNIR,abnormal pixel,bad pixels,dark vertical stripes,detection,error correction,geophysical measurement technique,hyperspectral remote sensing,image processing,infrared,land surface,multispectral remote sensing,satellite remote sensing,signal processing,terrain mapping,visible | Terrain mapping,Atmospheric correction,VNIR,Computer vision,Computer science,Remote sensing,Image processing,Error detection and correction,Pixel,Artificial intelligence,Geophysical signal processing | Conference |
Volume | Citations | PageRank |
3 | 12 | 3.26 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| tian han | 1 | 31 | 10.85 |
| david g goodenough | 2 | 78 | 18.64 |
| a dyk | 3 | 85 | 18.72 |
| Love, J. | 4 | 17 | 4.03 |