Efficient image correspondence measurements in airborne applications using inertial navigation sensors

Matthew Woods*, Aggelos Katsaggelos

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review


This paper presents a computationally efficient method for the measurement of a dense image correspondence vector field using supplementary data from an inertial navigation sensor. The application is suited to airborne imaging systems (such as on a UAV) where size, weight, and power restrictions limit the amount of onboard processing available. The limited processing will typically exclude the use of traditional, but expensive, optical flow algorithms such as Lucas-Kanade. Alternately, the measurements from an inertial navigation sensor lead to a closed-form solution to the correspondence field. Airborne platforms are also well suited to this application because they already possess inertial navigation sensors and global positioning systems (GPS) as part of their existing avionics package. We derive the closed form solution for the image correspondence vector field based on the inertial navigation sensor data. We then show experimentally that the inertial sensor solution outperforms traditional optical flow methods both in processing speed and accuracy.

Original languageEnglish (US)
Pages (from-to)606-610
Number of pages5
JournalEuropean Signal Processing Conference
StatePublished - 2010
Event18th European Signal Processing Conference, EUSIPCO 2010 - Aalborg, Denmark
Duration: Aug 23 2010Aug 27 2010

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering


Dive into the research topics of 'Efficient image correspondence measurements in airborne applications using inertial navigation sensors'. Together they form a unique fingerprint.

Cite this