Field Calibration of Hyperspectral Cameras for Terrain Inference
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arXiv
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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866908568231346176 |
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| author | Hanson, Nathaniel Pyatski, Benjamin Hibbard, Samuel Lvov, Gary De La Garza, Oscar DiMarzio, Charles Dorsey, Kristen L. Padır, Taşkın |
| author_facet | Hanson, Nathaniel Pyatski, Benjamin Hibbard, Samuel Lvov, Gary De La Garza, Oscar DiMarzio, Charles Dorsey, Kristen L. Padır, Taşkın |
| contents | Intra-class terrain differences such as water content directly influence a vehicle's ability to traverse terrain, yet RGB vision systems may fail to distinguish these properties. Evaluating a terrain's spectral content beyond red-green-blue wavelengths to the near infrared spectrum provides useful information for intra-class identification. However, accurate analysis of this spectral information is highly dependent on ambient illumination. We demonstrate a system architecture to collect and register multi-wavelength, hyperspectral images from a mobile robot and describe an approach to reflectance calibrate cameras under varying illumination conditions. To showcase the practical applications of our system, HYPER DRIVE, we demonstrate the ability to calculate vegetative health indices and soil moisture content from a mobile robot platform. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_25663 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Field Calibration of Hyperspectral Cameras for Terrain Inference Hanson, Nathaniel Pyatski, Benjamin Hibbard, Samuel Lvov, Gary De La Garza, Oscar DiMarzio, Charles Dorsey, Kristen L. Padır, Taşkın Robotics Image and Video Processing Intra-class terrain differences such as water content directly influence a vehicle's ability to traverse terrain, yet RGB vision systems may fail to distinguish these properties. Evaluating a terrain's spectral content beyond red-green-blue wavelengths to the near infrared spectrum provides useful information for intra-class identification. However, accurate analysis of this spectral information is highly dependent on ambient illumination. We demonstrate a system architecture to collect and register multi-wavelength, hyperspectral images from a mobile robot and describe an approach to reflectance calibrate cameras under varying illumination conditions. To showcase the practical applications of our system, HYPER DRIVE, we demonstrate the ability to calculate vegetative health indices and soil moisture content from a mobile robot platform. |
| title | Field Calibration of Hyperspectral Cameras for Terrain Inference |
| topic | Robotics Image and Video Processing |
| url | https://arxiv.org/abs/2509.25663 |