Processing Sparse Panoramic Images via Space Variant Operators

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1 Citation (Scopus)


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.
Original languageEnglish
Pages (from-to)349-361
JournalJournal of Mathematical Imaging and Vision
Issue number2
Publication statusPublished (in print/issue) - Nov 2008


  • Sparse images
  • Space variant operators
  • Omni-directional images


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