Hyperspectral and Lidar Intensity Data Fusion: A Framework for the Rigorous Correction of Illumination, Anisotropic Effects, and Cross Calibration
- The fusion of hyperspectral imaging (HSI) sensor and airborne lidar scanner (ALS) data provides promising potential for applications in environmental sciences. Standard fusion approaches use reflectance information from the HSI and distance measurements from the ALS to increase data dimen-sionality and geometric accuracy. However, the potential for data fusion based on the respective intensity information of the complementary active and passive sensor systems is high and not yet fully exploited. Here, an approach for the rigorous illumination correction of HSI data, based on the radiometric cross-calibrated return intensity information of ALS data, is presented. The cross calibration utilizes a ray tracing-based fusion of both sensor measurements by intersecting their particular beam shapes. The developed method is capable of compensating for the drawbacks of passive HSI systems, such as cast and cloud shadowing effects, illumination changes over time, across track illumination, and partly anisotropy effects. During processing,The fusion of hyperspectral imaging (HSI) sensor and airborne lidar scanner (ALS) data provides promising potential for applications in environmental sciences. Standard fusion approaches use reflectance information from the HSI and distance measurements from the ALS to increase data dimen-sionality and geometric accuracy. However, the potential for data fusion based on the respective intensity information of the complementary active and passive sensor systems is high and not yet fully exploited. Here, an approach for the rigorous illumination correction of HSI data, based on the radiometric cross-calibrated return intensity information of ALS data, is presented. The cross calibration utilizes a ray tracing-based fusion of both sensor measurements by intersecting their particular beam shapes. The developed method is capable of compensating for the drawbacks of passive HSI systems, such as cast and cloud shadowing effects, illumination changes over time, across track illumination, and partly anisotropy effects. During processing, spatial and temporal differences in illumination patterns are detected and corrected over the entire HSI wavelength domain. The improvement in the classification accuracy of urban and vegetation surfaces demonstrates the benefit and potential of the proposed HSI illumination correction. The presented approach is the first step toward the rigorous in-flight fusion of passive and active system characteristics, enabling new capabilities for a variety of applications.…
Verfasserangaben: | Maximilian BrellORCiDGND, Karl Segl, Luis Guanter, Bodo BookhagenORCiDGND |
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DOI: | https://doi.org/10.1109/TGRS.2017.2654516 |
ISSN: | 0196-2892 |
ISSN: | 1558-0644 |
Titel des übergeordneten Werks (Englisch): | IEEE transactions on geoscience and remote sensing |
Verlag: | Inst. of Electr. and Electronics Engineers |
Verlagsort: | Piscataway |
Publikationstyp: | Wissenschaftlicher Artikel |
Sprache: | Englisch |
Jahr der Erstveröffentlichung: | 2017 |
Erscheinungsjahr: | 2017 |
Datum der Freischaltung: | 20.04.2020 |
Freies Schlagwort / Tag: | Airborne laser scanning (ALS); deshadowing; imaging spectroscopy; in-flight; mosaicking; pixel-level fusion; preprocessing; radiometric alignment; ray tracing; sensor alignment; sensor fusion |
Band: | 55 |
Seitenanzahl: | 12 |
Erste Seite: | 2799 |
Letzte Seite: | 2810 |
Fördernde Institution: | Zentrales Innovationsprogramm Mittelstand" program founded by the Federal Ministry for Economic Affairs and Energy Germany; Helmholtz Centre Potsdam, GFZ German Research Centre for Geoscience |
Organisationseinheiten: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Geowissenschaften |
Peer Review: | Referiert |
Name der Einrichtung zum Zeitpunkt der Publikation: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Erd- und Umweltwissenschaften |