Multi-Scale Matching for the Automatic Location of Control Points in Large Scale Aerial Images Using Terrestrial Scenes

Abstract

ABSTRACT:A technique to automatically locate Ground Control Points (GCPs) in large aerial images is presented considering the availability of low accuracy direct georeferencing data. The approach is based on image chips of GCPs extracted from vertical terrestrial images. A strategy combining image matching techniques was implemented to select correct matches. These matches were used to define a 2D transformation with which the GCP is projected close to its correct position, reducing the search space in the aerial image. Area-based matching with some refinements is used to locate GCPs with sub-pixel precision. Experiments were performed with multi-scale images and assessed with a bundle block adjustment simulating an indirect sensor orientation. The accuracy analysis was accomplished based on discrepancies obtained from GCPs and check points. The results were better than interactive measurements and a planimetric accuracy of 1/5 of the Ground Sample Distance (GSD) for the check points was achieved.

A mobile platform with a catadioptric sensor

“…(1) camera calibration: this task was performed with existing 3D calibration field and software to which models for fisheye lens (equidistant with Conrady-Brown distortion coefficients) was included (Tommaselli et al, 2014);…”

“…This work has been driven by the generation of high resolution ground control chips aiming at indirect orientation of orbital images. The use of control chips was originally proposed by Malmström (1986) and it inspired a technique in which Terrestrial Control Chips were acquired by a fisheye lens camera (Tommaselli et al, 2013;Berveglieri and Tommaselli, 2014). Orientation of orbital images, mainly those with medium resolution, requires a more efficient technique for collecting ground information.…”