ReSVA: A MATLAB method to co-register and mosaic airborne video-based remotely sensed data

MethodsX. 2021 Jul 27:8:101471. doi: 10.1016/j.mex.2021.101471. eCollection 2021.

Abstract

Airborne remotely sensed data (e.g. hyperspectral imagery, thermal videography, full frame RGB photography) often requires post-processing to be combined into a series of images or a mosaic for analysis. This is generally accomplished through the use of position and attitude hardware (i.e. Global Navigation Satellite System - GNSS / Inertial Measurement Unit - IMU) in combination with specialized software. Occasionally, hardware failure in the GNSS/IMU instrumentation occurs, however the data are still recoverable through a correction process, which allows image registration to mosaic the data. Here we present a simple and flexible MATLAB® code package that has been developed to combine video-based remotely sensed data. It first applies an iterative image registration process to align all frames, using pre-existing GPS information if supplied by the user, and then grids the frame data together to develop a final, single mosaic dataset that can be used for analysis. An example of this method using airborne infrared video data of a wildfire is shown as a demonstration.•MATLAB functions are easily adaptable to specific user needs and datasets.•The method outputs the combined data and positional information in three separate MATLAB variables that can be readily used for analysis in MATLAB or exported for use in other software.

Keywords: Airborne survey; Geocorrection; Gridding; Image processing.