boost::gil::anisotropic_diffusion

Performs diffusion according to Perona‐Malik equation

Synopsis

Declared in <boost/gil/extension/image_processing/diffusion.hpp>

template<
    typename InputView,
    typename OutputView,
    typename LaplaceStrategy = laplace_function::stencil_9points_standard,
    typename BrightnessFunction = brightness_function::identity,
    typename DiffusivityFunction = conductivity::gaussian_conductivity>
void
anisotropic_diffusion(
    InputView const& input,
    OutputView const& output,
    unsigned int num_iter,
    LaplaceStrategy laplace,
    BrightnessFunction brightness,
    DiffusivityFunction diffusivity);

Description

WARNING: Output channel type must be floating point, otherwise there will be loss in accuracy which most probably will lead to incorrect results (input will be unchanged). Anisotropic diffusion is a smoothing algorithm that respects edge boundaries and can work as an edge detector if suitable iteration count is set and grayscale image view is used as an input

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