A Novel and Open-Source Illumination Correction for Hyperspectral Digital Outcrop Models

The widespread application of drones and associated miniaturization imaging sensors has led to an explosion remote sensing applications with very high spatial spectral resolutions. 3-D ultrahigh-resolution digital outcrop models created using oblique imagery from ground-based are now commonly used in the academic industrial sectors, while generation spatially accurate been greatly facilitated by development computer vision tools, such as structure motion, correction attributes achieve material reflectance measurements remains challenging. Following a topographical toolbox (mephysto), we propose series new tools that can leverage detailed geometry captured correct for illumination effects caused viewing angles interaction light complex surfaces. This open-source code is integrated into hylite, python full processing fusion hyperspectral data. We validate performance our novel method case study at open-pit mine Tharsis, Spain, demonstrate importance corrections quantitative analyses. Significantly, show applied analysis techniques yield erroneous results data corrected current state-of-the-art approaches. Our proposed ameliorates many issues these established