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Convolution

  • Alan Bundy
  • Lincoln Wallen
Part of the Symbolic Computation book series (SYMBOLIC)

Abstract

The application of a mathematical operation to each neighbourhood in an image is called convolution. The operation is defined by a “mask” specifying for each neighbourhood, how many points it contains and how the corresponding image point affects the computations. Each location in the operator mask contains a weighting value, these are multiplied by the value of the corresponding image location and the results summed to give the convolution value for that neighbourhood. Doing this for all neighbourhoods produces a new array of values. Mathematically, the convolution integral is the integrated cross product of a weighting function with an image. See local grey-level operations <127>.

Keywords

Data Item Image Point Modulation Transfer Function Mathematical Operation Normalise Description 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Reference

  1. [Frisby 79]
    Frisby, J. P. Seeing. Oxford University Press, 1979.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1984

Authors and Affiliations

  • Alan Bundy
    • 1
  • Lincoln Wallen
  1. 1.Department of Artificial IntelligenceEdinburgh UniversityEdinburghScotland

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