Journal of Mathematical Imaging and Vision

, Volume 32, Issue 3, pp 349–361

Processing Sparse Panoramic Images via Space Variant Operators


DOI: 10.1007/s10851-008-0107-0

Cite this article as:
Coleman, S., Scotney, B. & Kerr, D. J Math Imaging Vis (2008) 32: 349. doi:10.1007/s10851-008-0107-0


The use of omni-directional cameras has become increasingly popular in vision systems for video surveillance and autonomous robot navigation. However, to date most of the research relating to omni-directional cameras has focussed on the design of the camera or the way in which to project the omni-directional image to a panoramic view rather than the processing of such images after capture. Typically images obtained from omni-directional cameras are transformed to sparse panoramic images that are interpolated to obtain a complete panoramic view prior to low level image processing. This interpolation presents a significant computational overhead with respect to real-time vision.

We present an efficient design procedure for space variant feature extraction operators that can be applied to a sparse panoramic image and directly processes this sparse image. This paper highlights the reduction of the computational overheads of directly processing images arising from omni-directional cameras through efficient coding and storage, whilst retaining accuracy sufficient for application to real-time robot vision.


Sparse imagesSpace variant operatorsOmni-directional images

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  1. 1.School of Computing and Intelligent SystemsUniversity of UlsterLondonderryNorthern Ireland
  2. 2.School of Computing and Information EngineeringUniversity of UlsterColeraineNorthern Ireland