CoastalLens: A MATLAB UAV Video Stabilization &Rectification Framework

Uncrewed aerial vehicles (UAVs) are an important tool for coastal monitoring with their relatively low-cost and rapid deployment capabilities.To generate scientific-grade image products, to use for wave runup observations, for bathymetry inversions, or tracking surfzone currents, the hovering UAV images/videos must be stabilized and rectified into world coordinates.Video stabilization is an active area of research and is use in many fields including videography, law enforcement, and agriculture (see (Wilko Guilluy et al., 2021), (Yiming Wang et al., 2023) for reviews on video stabilization).Due to the limited stationary region of coastal images suitable for control points, the processing of coastal UAV-obtained videos can be time-consuming and resource-intensive.The CIRN Qualitative Coastal Imagining Toolbox (Bruder & Brodie, 2020) provided a first-of-its-kind open-sourced code for rectifying these coastal UAV videos.Limitations of the toolbox, however, prompted the development of CoastalLens with an efficient data input procedure, providing capabilities to obtain drone position (extrinsics) from LiDAR surveys, and using a feature detection and matching algorithm to stabilize the video prior to rectification.This framework reduces the amount of human oversight, now only required during the data input processes.Removing the dependency on threshold stability control points provides more stable results and can also result in less time in the field.We hope this framework will allow for more efficient processing of the ever-increasing coastal UAV datasets.