Underwater 3d Modeling: Image Enhancement and Point Cloud Filtering

Abstract

ABSTRACT:This paper examines the results of image enhancement and point cloud filtering on the visual and geometric quality of 3D models for the representation of underwater features. Specifically it evaluates the combination of effects from the manual editing of images' radiometry (captured at shallow depths) and the selection of parameters for point cloud definition and mesh building (processed in 3D modeling software). Such datasets, are usually collected by divers, handled by scientists and used for geovisualization purposes. In the presented study, have been created 3D models from three sets of images (seafloor, part of a wreck and a small boat's wreck) captured at three different depths (3.5m, 10m and 14m respectively). Four models have been created from the first dataset (seafloor) in order to evaluate the results from the application of image enhancement techniques and point cloud filtering. The main process for this preliminary study included a) the definition of parameters for the point cloud filtering and the creation of a reference model, b) the radiometric editing of images, followed by the creation of three improved models and c) the assessment of results by comparing the visual and the geometric quality of improved models versus the reference one. Finally, the selected technique is tested on two other data sets in order to examine its appropriateness for different depths (at 10m and 14m) and different objects (part of a wreck and a small boat's wreck) in the context of an ongoing research in the Laboratory of Photogrammetry and Remote Sensing.

Review of the state of practice in geovisualization in the geosciences

“…Modelling software has been used for active events and simulations such as landslides, flooding mitigation, and rockfalls (Jacquinod and Julia Bonaccorsi, 2019;Forsythe et al, 2021;Nordvik et al, 2009;Zhang et al, 2020). It has also been used in static instances to create more in depth maps and 3D recreations of coastlines, bathymetry, and terrain (Sarakinou et al, 2016;Papakonstantinou et al, 2018;Papadopoulou et al, 2021;de Magalhaes et al, 2020).…”

“…Data collected for pseudo 3D is being represented in the form of digital elevation models (DEM), hillshades, slope maps, triangular irregular networks (TIN), among others. However, 3D data is now being represented with all three coordinates (x, y, z) in the form of point clouds, generally collected using Light Detection and Ranging (LiDAR) (Sarakinou et al, 2016).…”

PCA-Based Denoising Algorithm for Outdoor Lidar Point Cloud Data

“…With the development of three-dimensional (3D) technologies, lidar has gained increasing attention due to its low price, small size, and high precision. In recent years, lidars have been widely used in autonomous driving [ 1 , 2 , 3 ], aerospace [ 4 ], three-dimensional modeling [ 5 , 6 , 7 , 8 ], and other fields. In these applications, lidars provide the range map of the concerned object or environment, which can be further processed for geological mapping [ 9 , 10 , 11 ], simultaneous localization and mapping (SLAM) [ 12 , 13 , 14 , 15 , 16 , 17 , 18 ], as well as 3D modeling and reconstruction, even for the modeling of human organs, detection and positioning of necrotic tissues, and other aspects in medicine [ 19 ].…”

Detecting change in coral reef 3D structure using underwater photogrammetry: critical issues and performance metrics

“…In recent years, thanks to the use of Structure-from-Motion (SfM) photogrammetry, images acquired by unmanned underwater vehicle and divers can be used for the reconstruction of geomorphic features, archeological sites, and benthic communities at cm-to-mm spatial resolution, depending on the camera settings used and the distance to the imaged object (Capra et al 2017(Capra et al , 2015Drap et al 2013;Sarakinou et al 2016). The general SfM workflow and the achievable accuracy have been documented in many papers based on aerial and ground-based surveys (see Agüera-Vega et al 2016;Eltner et al 2016;Fonstad et al 2013;Harwin et al 2015;Mancini et al 2013;Nex and Remondino 2014;Rupnik et al 2014;Toschi et al 2013 among others).…”