Name
Title | ||
|---|---|---|
Reduction of Uncorrelated Striping Noise—Applications for Hyperspectral Pushbroom Acquisitions |
Abstract | ||
|---|---|---|
Hyperspectral images are of increasing importance in remote sensing applications. Imaging spectrometers provide semi-continuous spectra that can be used for physics based surface cover material identification and quantification. Preceding radiometric calibrations serve as a basis for the transformation of measured signals into physics based units such as radiance. Pushbroom sensors collect incident radiation by at least one detector array utilizing the photoelectric effect. Temporal variations of the detector characteristics that differ with foregoing radiometric calibration cause visually perceptible along-track stripes in the at-sensor radiance data that aggravate succeeding image-based analyses. Especially, variations of the thermally induced dark current dominate and have to be reduced. In this work, a new approach is presented that efficiently reduces dark current related stripe noise. It integrates an across-effect gradient minimization principle. The performance has been evaluated using artificially degraded whiskbroom (reference) and real pushbroom acquisitions from EO-1 Hyperion and AISA DUAL that are significantly covered by stripe noise. A set of quality indicators has been used for the accuracy assessment. They clearly show that the new approach outperforms a limited set of tested state-of-the-art approaches and achieves a very high accuracy related to ground-truth for selected tests. It may substitute recent algorithms in the Reduction of Miscalibration Effects (ROME) framework that is broadly used to reduce radiometric miscalibrations of pushbroom data takes. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.3390/rs61111082 | REMOTE SENSING |
Keywords | Field | DocType |
stripes,hyperspectral,dark current,pushbroom,calibration,radiometric,EO-1 Hyperion,AISA,EnMAP,ROME | Radiometric calibration,Computer vision,Remote sensing,Remote sensing application,Dark current,Hyperspectral imaging,Artificial intelligence,EnMAP,Geology,Detector,Calibration,Radiance | Journal |
Volume | Issue | ISSN |
6 | 11 | 2072-4292 |
Citations | PageRank | References |
8 | 0.61 | 19 |
Authors | ||
11 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| christian rogass | 1 | 159 | 14.52 |
| christian mielke | 2 | 26 | 2.59 |
| daniel scheffler | 3 | 8 | 0.61 |
| nina boesche | 4 | 26 | 2.59 |
| Angela Lausch | 5 | 46 | 6.76 |
| Christin Lubitz | 6 | 24 | 3.62 |
| maximilian brell | 7 | 15 | 1.51 |
| Daniel Spengler | 8 | 51 | 6.70 |
| andreas eisele | 9 | 8 | 0.61 |
| Karl Segl | 10 | 315 | 39.58 |
| Luis Guanter | 11 | 373 | 42.94 |