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.…
Author details: | Maximilian BrellORCiDGND, Karl Segl, Luis Guanter, Bodo BookhagenORCiDGND |
---|---|
DOI: | https://doi.org/10.1109/TGRS.2017.2654516 |
ISSN: | 0196-2892 |
ISSN: | 1558-0644 |
Title of parent work (English): | IEEE transactions on geoscience and remote sensing |
Publisher: | Inst. of Electr. and Electronics Engineers |
Place of publishing: | Piscataway |
Publication type: | Article |
Language: | English |
Year of first publication: | 2017 |
Publication year: | 2017 |
Release date: | 2020/04/20 |
Tag: | Airborne laser scanning (ALS); deshadowing; imaging spectroscopy; in-flight; mosaicking; pixel-level fusion; preprocessing; radiometric alignment; ray tracing; sensor alignment; sensor fusion |
Volume: | 55 |
Number of pages: | 12 |
First page: | 2799 |
Last Page: | 2810 |
Funding 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 |
Organizational units: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Geowissenschaften |
Peer review: | Referiert |
Institution name at the time of the publication: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Erd- und Umweltwissenschaften |