Abstract
The objective of this investigation is to develop and test a radiometric correction process for UAV image blocks. The phases of the process include the laboratory calibration of the sensor and the radiometric correction of the campaign image data. This investigation focuses on developing a process for radiometric correction of the image data collected during a remote sensing campaign. First of all, the orientations for the images are determined using the self-calibrating bundle block adjustment method and an accurate DSM is generated by automatic image matching. The varying radiometric level of images due to changes in illumination and the instability of the sensor are eliminated using a relative radiometric block adjustment technique. Optional reflectance reference observations can be used to adjust the data to absolute reflectance units. The process was demonstrated and evaluated by using two UAV imaging systems: a consumer camera-based system and a novel Fabry-Perot interferometer-based next generation light-weight hyperspectral imaging system. The method improved the homogeneity of the data, but some drift also appeared in the parameters. The first experiment provided 0.003–0.008 reflectance errors in the areas close to the radiometric control points (mostly on the level of 5 % of the reflectance value). The presented approach provides a general framework for rigorous radiometric correction of UAV image blocks, and the novel technology provides many possibilities for the further development of the method. Our results also show that hyperspectral stereophotogrammetry is now possible with UAV imaging sensors weighing less than 500 g.
Original language | English |
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Pages (from-to) | 115-127 |
Journal | Photogrammetrie, Fernerkundung, Geoinformation |
Issue number | 2 |
DOIs | |
Publication status | Published - 2012 |
MoE publication type | A1 Journal article-refereed |
Keywords
- Hyperspectral sensors
- multispectral image sensors
- Fabry-Perot Interferometer
- Piezo actuators
- imaging spectrometer
- UAV
- airborne
- medical imaging
- presision agriculture
- target detection