diplib/deconvolution.h file

Functions

void dip::WienerDeconvolution(dip::Image const& in, dip::Image const& psf, dip::Image const& signalPower, dip::Image const& noisePower, dip::Image& out, dip::StringSet const& options = {S::PAD})

Wiener deconvolution using estimates of signal and noise power spectra.

void dip::WienerDeconvolution(dip::Image const& in, dip::Image const& psf, dip::Image& out, dip::dfloat regularization = 1e-4, dip::StringSet const& options = {S::PAD})

Wiener deconvolution using an estimate of noise-to-signal ratio.

void dip::TikhonovMiller(dip::Image const& in, dip::Image const& psf, dip::Image& out, dip::dfloat regularization = 0.1, dip::StringSet const& options = {S::PAD})

Tikhonov-Miller deconvolution.

void dip::IterativeConstrainedTikhonovMiller(dip::Image const& in, dip::Image const& psf, dip::Image& out, dip::dfloat regularization = 0.1, dip::dfloat tolerance = 1e-6, dip::uint maxIterations = 30, dip::dfloat stepSize = 0.0, dip::StringSet const& options = {S::PAD})

Iterative Constrained Tikhonov-Miller (ICTM) deconvolution.

void dip::RichardsonLucy(dip::Image const& in, dip::Image const& psf, dip::Image& out, dip::dfloat regularization = 0.0, dip::uint nIterations = 30, dip::StringSet const& options = {S::PAD})

Richardson-Lucy (RL) deconvolution, also sometimes called the expectation maximization (EM) method.

void dip::FastIterativeShrinkageThresholding(dip::Image const& in, dip::Image const& psf, dip::Image& out, dip::dfloat regularization = 0.1, dip::dfloat tolerance = 1e-6, dip::uint maxIterations = 30, dip::uint nScales = 3, dip::StringSet const& options = {S::PAD})

Fast Iterative Shrinkage-Thresholding (FISTA) deconvolution.