Improving Local Adaptive Filtering Method Employed in Radiometric Correction of Analogue Airborne Campaigns

Abstract

Abstract. An orthophotomosaic is as a single image that can be layered on a map. It is produced from a set of aerial images impaired by radiometric inhomogeneity mostly due to atmospheric phenomena, like hotspot, haze or high altitude clouds shadows as well as the camera itself, like lens vignetting. These create some unsightly radiometric inhomogeneity in the mosaic that could be corrected by using a local adaptive filter, also named Wallis filter. Yet this solution leads to a significant loss of contrast at small scales. This current work introduces two elementary studies. In a first time, in order to quantify the loss of contrast due to the use of Wallis filter, a simple multi-scale score is proposed based on mathematical morphology operations. In a second time, an optimal window size for the filter is identified by considering some systematic radiometric behaviours in the images forming the mosaic through Principal Component Analysis (PCA). These two elementary studies are preliminary steps leading to a method of radiometric correction combining Wallis filtering and PCA.

Multi-Modal Geospatial and Thematic Data to Foster Green Deal Applications

“…• aerial image triangulation with learning-based features (Remondino et al, 2022); • co-registration of multi-modal and multi-spectral images (Ruiz de Ona et al, 2023); • co-registration of LiDAR and optical data (Toschi et al, 2021); • evaluate production pipeline solutions for large-scale mapping purposes (Moe et al, 2016;Toschi et al, 2017); • evaluation of conventional or learning-based MVS / dense image matching methods (Chebbi et al, 2023;Liu et al, 2023;Stathopoulou and Remondino, 2023); • NeRF-based 3D reconstruction (Turki et al, 2022;Remondino et al, 2023;); • automatic radiometric correction of large-size orthophotos (Lelégard et al 2022). Furthermore, the datasets could be valuable for the realization and validation of algorithms for the generation of other (geo)products to support Green Deal policies, such as:…”