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Influence of blur on feature matching and a geometric approach for photogrammetric deblurring

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conference contribution
posted on 23.10.2014, 13:09 by Till Sieberth, Rene Wackrow, Jim Chandler
Unmanned aerial vehicles (UAV) have become an interesting and active research topic for photogrammetry. Current research is based on images acquired by a UAV, which have a high ground resolution and good spectral and radiometric resolution, due to the low flight altitudes combined with a high resolution camera. UAV image flights are also cost efficient and have become attractive for many applications including change detection in small scale areas. One of the main problems preventing full automation of data processing of UAV imagery is the degradation effect of blur caused by camera movement during image acquisition. This can be caused by the normal flight movement of the UAV as well as strong winds, turbulence or sudden operator inputs. This blur disturbs the visual analysis and interpretation of the data, causes errors and can degrade the accuracy in automatic photogrammetric processing algorithms. The aim of this research is to develop a blur correction method to deblur UAV images. Deblurring of images is a widely researched topic and often based on the Wiener or Richardson-Lucy deconvolution, which require precise knowledge of both the blur path and extent. Even with knowledge about the blur kernel, the correction causes errors such as ringing, and the deblurred image appears "muddy" and not completely sharp. In the study reported in this paper, overlapping images are used to support the deblurring process, which is advantageous. An algorithm based on the Fourier transformation is presented. This works well in flat areas, but the need for geometrically correct sharp images may limit the application. Deblurring images needs to focus on geometric correct deblurring to assure geometric correct measurements.

History

School

  • Architecture, Building and Civil Engineering

Published in

Photogrammetric Computer Vision 2014 ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences

Volume

XL-3

Pages

321 - 326 (6)

Citation

SIEBERTH, T., WACKROW, R. and CHANDLER, J., 2014. Influence of blur on feature matching and a geometric approach for photogrammetric deblurring. IN: Schindler, K. and Paparoditis, N. (eds). The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-3, 2014. ISPRS Technical Commission III Symposium, 5 – 7 September 2014, Zurich, Switzerland, pp.321-326.

Publisher

ISPRS

Version

VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2014

Notes

This is a conference paper. It was originally published at: http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-3/321/2014/isprsarchives-XL-3-321-2014.pdf

Language

en

Location

Zurich, Switzerland