diplib/linear.h file

Functions that implement linear filters. See Linear filters.

Contents

Classes

struct dip::OneDimensionalFilter
Describes a 1D filter

Aliases

using dip::OneDimensionalFilterArray = std::vector<OneDimensionalFilter>
An array of 1D filters

Functions

auto dip::SeparateFilter(dip::Image const& filter) -> dip::OneDimensionalFilterArray
Separates a linear filter (convolution kernel) into a set of 1D filters that can be applied using dip::SeparableConvolution.
void dip::SeparableConvolution(dip::Image const& in, dip::Image& out, dip::OneDimensionalFilterArray const& filterArray, dip::StringArray const& boundaryCondition = {}, dip::BooleanArray process = {})
Applies a convolution with a filter kernel (PSF) that is separable.
void dip::ConvolveFT(dip::Image const& in, dip::Image const& filter, dip::Image& out, dip::String const& inRepresentation = S::SPATIAL, dip::String const& filterRepresentation = S::SPATIAL, dip::String const& outRepresentation = S::SPATIAL)
Applies a convolution with a filter kernel (PSF) by multiplication in the Fourier domain.
void dip::GeneralConvolution(dip::Image const& in, dip::Image const& filter, dip::Image& out, dip::StringArray const& boundaryCondition = {})
Applies a convolution with a filter kernel (PSF) by direct implementation of the convolution sum.
void dip::Uniform(dip::Image const& in, dip::Image& out, dip::Kernel const& kernel = {}, dip::StringArray const& boundaryCondition = {})
Applies a convolution with a kernel with uniform weights, leading to an average (mean) filter.
void dip::GaussFIR(dip::Image const& in, dip::Image& out, dip::FloatArray sigmas = {1.0}, dip::UnsignedArray derivativeOrder = {0}, dip::StringArray const& boundaryCondition = {}, dip::dfloat truncation = 3)
Finite impulse response implementation of the Gaussian filter and its derivatives
void dip::GaussFT(dip::Image const& in, dip::Image& out, dip::FloatArray sigmas = {1.0}, dip::UnsignedArray derivativeOrder = {0}, dip::dfloat truncation = 3)
Fourier implementation of the Gaussian filter and its derivatives
void dip::GaussIIR(dip::Image const& in, dip::Image& out, dip::FloatArray sigmas = {1.0}, dip::UnsignedArray derivativeOrder = {0}, dip::StringArray const& boundaryCondition = {}, dip::UnsignedArray filterOrder = {}, dip::String const& designMethod = S::DISCRETE_TIME_FIT, dip::dfloat truncation = 3)
Infinite impulse response implementation of the Gaussian filter and its derivatives
void dip::Gauss(dip::Image const& in, dip::Image& out, dip::FloatArray sigmas = {1.0}, dip::UnsignedArray derivativeOrder = {0}, dip::String const& method = S::BEST, dip::StringArray const& boundaryCondition = {}, dip::dfloat truncation = 3)
Convolution with a Gaussian kernel and its derivatives
void dip::FiniteDifference(dip::Image const& in, dip::Image& out, dip::UnsignedArray derivativeOrder = {0}, dip::String const& smoothFlag = S::SMOOTH, dip::StringArray const& boundaryCondition = {}, dip::BooleanArray process = {})
Finite difference derivatives
void dip::SobelGradient(dip::Image const& in, dip::Image& out, dip::uint dimension = 0, dip::StringArray const& boundaryCondition = {})
The Sobel derivative filter
void dip::Derivative(dip::Image const& in, dip::Image& out, dip::UnsignedArray derivativeOrder, dip::FloatArray sigmas = {1.0}, dip::String const& method = S::BEST, dip::StringArray const& boundaryCondition = {}, dip::dfloat truncation = 3)
Computes derivatives
void dip::Dx(dip::Image const& in, dip::Image& out, dip::FloatArray sigmas = {1.0})
Computes the first derivative along x, see dip::Derivative.
void dip::Dy(dip::Image const& in, dip::Image& out, dip::FloatArray sigmas = {1.0})
Computes the first derivative along y, see dip::Derivative.
void dip::Dz(dip::Image const& in, dip::Image& out, dip::FloatArray sigmas = {1.0})
Computes the first derivative along z, see dip::Derivative.
void dip::Dxx(dip::Image const& in, dip::Image& out, dip::FloatArray sigmas = {1.0})
Computes the second derivative along x, see dip::Derivative.
void dip::Dyy(dip::Image const& in, dip::Image& out, dip::FloatArray sigmas = {1.0})
Computes the second derivative along y, see dip::Derivative.
void dip::Dzz(dip::Image const& in, dip::Image& out, dip::FloatArray sigmas = {1.0})
Computes the second derivative along z, see dip::Derivative.
void dip::Dxy(dip::Image const& in, dip::Image& out, dip::FloatArray sigmas = {1.0})
Computes the first derivative along x and y, see dip::Derivative.
void dip::Dxz(dip::Image const& in, dip::Image& out, dip::FloatArray sigmas = {1.0})
Computes the first derivative along x and z, see dip::Derivative.
void dip::Dyz(dip::Image const& in, dip::Image& out, dip::FloatArray sigmas = {1.0})
Computes the first derivative along y and y, see dip::Derivative.
void dip::Gradient(dip::Image const& in, dip::Image& out, dip::FloatArray sigmas = {1.0}, dip::String const& method = S::BEST, dip::StringArray const& boundaryCondition = {}, dip::BooleanArray process = {}, dip::dfloat truncation = 3)
Computes the gradient of the image, resulting in an N-vector image, if the input was N-dimensional.
void dip::GradientMagnitude(dip::Image const& in, dip::Image& out, dip::FloatArray sigmas = {1.0}, dip::String const& method = S::BEST, dip::StringArray const& boundaryCondition = {}, dip::BooleanArray process = {}, dip::dfloat truncation = 3)
Computes the gradient magnitude of the image, equivalent to dip::Norm( dip::Gradient( in )).
void dip::GradientDirection(dip::Image const& in, dip::Image& out, dip::FloatArray sigmas = {1.0}, dip::String const& method = S::BEST, dip::StringArray const& boundaryCondition = {}, dip::BooleanArray process = {}, dip::dfloat truncation = 3)
Computes the direction of the gradient of the image, equivalent to dip::Angle( dip::Gradient( in )).
void dip::Curl(dip::Image const& in, dip::Image& out, dip::FloatArray sigmas = {1.0}, dip::String const& method = S::BEST, dip::StringArray const& boundaryCondition = {}, dip::BooleanArray process = {}, dip::dfloat truncation = 3)
Computes the curl (rotation) of the 2D or 3D vector field in.
void dip::Divergence(dip::Image const& in, dip::Image& out, dip::FloatArray sigmas = {1.0}, dip::String const& method = S::BEST, dip::StringArray const& boundaryCondition = {}, dip::BooleanArray process = {}, dip::dfloat truncation = 3)
Computes the divergence of the vector field in.
void dip::Hessian(dip::Image const& in, dip::Image& out, dip::FloatArray sigmas = {1.0}, dip::String const& method = S::BEST, dip::StringArray const& boundaryCondition = {}, dip::BooleanArray process = {}, dip::dfloat truncation = 3)
Computes the Hessian of the image, resulting in a symmetric NxN tensor image, if the input was N-dimensional.
void dip::Laplace(dip::Image const& in, dip::Image& out, dip::FloatArray sigmas = {1.0}, dip::String const& method = S::BEST, dip::StringArray const& boundaryCondition = {}, dip::BooleanArray process = {}, dip::dfloat truncation = 3)
Computes the Laplacian of the image, equivalent to dip::Trace( dip::Hessian( in )), but more efficient.
void dip::Dgg(dip::Image const& in, dip::Image& out, dip::FloatArray sigmas = {1.0}, dip::String const& method = S::BEST, dip::StringArray const& boundaryCondition = {}, dip::BooleanArray process = {}, dip::dfloat truncation = 3)
Computes the second derivative in the gradient direction.
void dip::LaplacePlusDgg(dip::Image const& in, dip::Image& out, dip::FloatArray sigmas = {1.0}, dip::String const& method = S::BEST, dip::StringArray const& boundaryCondition = {}, dip::BooleanArray process = {}, dip::dfloat truncation = 3)
Adds the second derivative in the gradient direction to the Laplacian.
void dip::LaplaceMinusDgg(dip::Image const& in, dip::Image& out, dip::FloatArray sigmas = {1.0}, dip::String const& method = S::BEST, dip::StringArray const& boundaryCondition = {}, dip::BooleanArray process = {}, dip::dfloat truncation = 3)
Subtracts the second derivative in the gradient direction from the Laplacian.
void dip::Sharpen(dip::Image const& in, dip::Image& out, dip::dfloat weight = 1.0, dip::FloatArray sigmas = {1.0}, dip::String const& method = S::BEST, dip::StringArray const& boundaryCondition = {}, dip::dfloat truncation = 3)
Sharpens in by subtracting the Laplacian of the image.
void dip::UnsharpMask(dip::Image const& in, dip::Image& out, dip::dfloat weight = 1.0, dip::FloatArray sigmas = {1.0}, dip::String const& method = S::BEST, dip::StringArray const& boundaryCondition = {}, dip::dfloat truncation = 3)
Sharpens in by subtracting the smoothed image.
void dip::GaborFIR(dip::Image const& in, dip::Image& out, dip::FloatArray sigmas, dip::FloatArray const& frequencies, dip::StringArray const& boundaryCondition = {}, dip::BooleanArray process = {}, dip::dfloat truncation = 3)
Finite impulse response implementation of the Gabor filter
void dip::GaborIIR(dip::Image const& in, dip::Image& out, dip::FloatArray sigmas, dip::FloatArray const& frequencies, dip::StringArray const& boundaryCondition = {}, dip::BooleanArray process = {}, dip::IntegerArray filterOrder = {}, dip::dfloat truncation = 3)
Recursive infinite impulse response implementation of the Gabor filter
void dip::Gabor2D(dip::Image const& in, dip::Image& out, dip::FloatArray sigmas = {5.0,5.0}, dip::dfloat frequency = 0.1, dip::dfloat direction = dip::pi, dip::StringArray const& boundaryCondition = {}, dip::dfloat truncation = 3)
2D Gabor filter with direction parameter
void dip::LogGaborFilterBank(dip::Image const& in, dip::Image& out, dip::FloatArray const& wavelengths = {3.0,6.0,12.0,24.0}, dip::dfloat bandwidth = 0.75, dip::uint nOrientations = 6, dip::String const& inRepresentation = S::SPATIAL, dip::String const& outRepresentation = S::SPATIAL)
Applies a log-Gabor filter bank
void dip::NormalizedConvolution(dip::Image const& in, dip::Image const& mask, dip::Image& out, dip::FloatArray const& sigmas = {1.0}, dip::String const& method = S::BEST, dip::StringArray const& boundaryCondition = {S::ADD_ZEROS}, dip::dfloat truncation = 3)
Computes the normalized convolution with a Gaussian kernel: a Gaussian convolution for missing or uncertain data.
void dip::NormalizedDifferentialConvolution(dip::Image const& in, dip::Image const& mask, dip::Image& out, dip::uint dimension = 0, dip::FloatArray const& sigmas = {1.0}, dip::String const& method = S::BEST, dip::StringArray const& boundaryCondition = {S::ADD_ZEROS}, dip::dfloat truncation = 3)
Computes the normalized differential convolution with a Gaussian kernel: a derivative operator for missing or uncertain data.
void dip::MeanShiftVector(dip::Image const& in, dip::Image& out, dip::FloatArray sigmas = {1.0}, dip::String const& method = S::BEST, dip::StringArray const& boundaryCondition = {}, dip::dfloat truncation = 3)
Computes the mean shift vector for each pixel in the image