VIGRA - Functions to Convolve Images and Signals

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| Functions to Convolve Images and Signals |
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1D and 2D filters, including separable and recursive convolution, and non-linear diffusion

#include "vigra/convolution.hxx"
Namespace: vigra

Common Filters
  Short-hands for the most common 2D convolution filters
Convolution filters for multi-dimensional arrays.
  Convolution filters for arbitrary dimensional arrays (MultiArray etc.)
Resampling Convolution Filters
  Resampling convolution filters
Two-dimensional convolution functions
  2D non-separable convolution, with and without ROI mask
vigra::Kernel2D
  Generic 2-dimensional discrete convolution kernel
One-dimensional and separable convolution functions
  1D convolution and separable filters in 2 dimensions
vigra::Kernel1D
  Generic 1-dimensional discrete convolution kernel
Recursive convolution functions
  Recursive filters (1st and 2nd order)
Non-linear Diffusion
  Edge-preserving smoothing
BorderTreatmentMode
  Choose between different border treatment modes
Kernel Argument Object Factories
  Factory functions to create argument objects to simplify passing kernels

© Ullrich Köthe (koethe@informatik.uni-hamburg.de) Cognitive Systems Group, University of Hamburg, Germany | html generated using doxygen and Python VIGRA 1.5.0 (7 Dec 2006)