Experimental Tests and Simulations on Correction Models for the Rolling Shutter Effect in UAV Photogrammetry

Author:

Bruno Nazarena1ORCID,Forlani Gianfranco1ORCID

Affiliation:

1. Department of Engineering and Architecture, University of Parma, Parco Area delle Scienze, 181/a, 43124 Parma, Italy

Abstract

Many unmanned aerial vehicles (UAV) host rolling shutter (RS) cameras, i.e., cameras where image rows are exposed at slightly different times. As the camera moves in the meantime, this causes inconsistencies in homologous ray intersections in the bundle adjustment, so correction models have been proposed to deal with the problem. This paper presents a series of test flights and simulations performed with different UAV platforms at varying speeds over terrain of various morphologies with the objective of investigating and possibly optimising how RS correction models perform under different conditions, in particular as far as block control is concerned. To this aim, three RS correction models have been applied in various combinations, decreasing the number of fixed ground control points (GCP) or exploiting GNSS-determined camera stations. From the experimental tests as well as from the simulations, four conclusions can be drawn: (a) RS affects primarily horizontal coordinates and varies notably from platform to platform; (b) if the ground control is dense enough, all correction models lead practically to the same mean error on checkpoints; however, some models may cause large errors in elevation if too few GCP are used; (c) in most cases, a specific correction model is not necessary since the affine deformation caused by RS can be adequately modelled by just applying the extended Fraser camera calibration model; (d) using GNSS-assisted block orientation, the number of necessary GCP is strongly reduced.

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

Reference33 articles.

1. Hartley, R., and Zisserman, A. (2000). Multiple View Geometry in Computer Vision, Cambridge University Press. [2nd ed.].

2. State of the art in high density image matching;Remondino;Photogramm. Rec.,2014

3. Deep convolutional neural networks for building extraction from orthoimages and dense image matching point clouds;Maltezos;J. Appl. Remote Sens.,2017

4. Eisenbeiß, H. (2009). UAV Photogrammetry, ETH ZURICH.

5. Review of CMOS image sensors;Bigas;Microelectron. J.,2006

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