• DocumentCode
    3398279
  • Title

    Image georegistration methods: A framework for application guidelines

  • Author

    Doucette, Peter ; Antonisse, Jim ; Braun, Aaron ; Lenihan, Michael ; Brennan, Michelle

  • Author_Institution
    Nat. Geospatial-Intell. Agency (NGA), Springfield, VA, USA
  • fYear
    2013
  • fDate
    23-25 Oct. 2013
  • Firstpage
    1
  • Lastpage
    14
  • Abstract
    With the rapid growth of sensor platforms for imagery collection, from micro-unmanned aerial systems (UAS) to smart phones, an ability to geo-register image data is a fundamental need for many downstream applications. Approaches to georegistration for sensor imagery have deep roots in photogrammetry, and more recently with the integration of computer vision techniques. Georegistration solutions are increasingly sought for inexpensive and non-metric quality sensors and/or those that may lack the metadata needed to support rigorous coordinate transfer with error estimation. This indicates a range of solution quality, with situational awareness at one end, and rigorous accuracy at the other. There are a variety of correspondence and transformation models from which to select, with tradeoffs among simplicity, accuracy, and error estimation. The continually expanding vernacular of terms and methods can lead to confusion of application among the broader community of users. A sorting of representative terminology, processes, and techniques, is proposed as a framework. The goal is to motivate discussion for application guidelines.
  • Keywords
    autonomous aerial vehicles; computer vision; image registration; UAS; computer vision techniques; image georegistration methods; imagery collection; micro-unmanned aerial systems; photogrammetry; rigorous coordinate transfer; sensor imagery; situational awareness; smart phones; Accuracy; Geometry; Global Positioning System; Image resolution; Imaging; Measurement units; Receivers; computer vision; error estimation; georegistration; image correspondence; photogrammetry; transformation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Applied Imagery Pattern Recognition Workshop (AIPR): Sensing for Control and Augmentation, 2013 IEEE
  • Conference_Location
    Washington, DC
  • Type

    conf

  • DOI
    10.1109/AIPR.2013.6749317
  • Filename
    6749317