imageFilters.hpp File Reference

Image filters (smoothing, radial profiles, etc.). More...

Image filters (smoothing, radial profiles, etc.).

Author

Jared R. Males (jared.nosp@m.male.nosp@m.s@gma.nosp@m.il.c.nosp@m.om)

Definition in file imageFilters.hpp.

#include <algorithm>
#include <cmath>
#include <cstdlib>
#include <format>
#include <limits>
#include "../math/floatUtils.hpp"
#include "../math/gslInterpolator.hpp"
#include "../math/vectorUtils.hpp"
#include "../math/geo.hpp"
#include "imageMasks.hpp"

Go to the source code of this file.

Classes
struct	mx::improc::gaussKernel< _arrayT, _kernW, _verboseT >
	Symetric Gaussian smoothing kernel. More...
struct	mx::improc::azBoxKernel< _arrayT, _kernW, _verboseT >
	Azimuthally variable boxcar kernel. More...
struct	mx::improc::precalcKernel< kernelT >
	A kernel that is pre-calculated for the entire image, useful for repeated applications. More...

Namespaces
namespace	mx
	The mxlib c++ namespace.

Functions
template<typename imageOutT, typename imageInT, typename kernelT>
error_t	mx::improc::filterImage (imageOutT &fim, imageInT im, const kernelT &kernel, int maxr=0)
	Filter an image with a mean kernel.
template<typename imageOutT, typename imageInT, typename kernelT>
void	mx::improc::medianFilterImage (imageOutT &fim, imageInT im, const kernelT &kernel, int maxr=0, int maxrproc=1)
	Filter an image with a median kernel.
template<typename imageTout, typename imageTin>
int	mx::improc::meanSmooth (imageTout &imOut, const imageTin &imIn, int meanFullWidth, bool rejectMinMax=false)
	Smooth an image using the mean in a rectangular box, optionally rejecting the highest and lowest values.
template<typename imageTout, typename imageTin>
int	mx::improc::meanSmooth (imageTout &imOut, int &xMax, int &yMax, typename imageTout::Scalar &pMax, const imageTin &imIn, int meanFullWidth, bool rejectMinMax=false)
	Smooth an image using the mean in a rectangular box, optionally rejecting the highest and lowest values. Determines the location and value of the highest pixel.
template<typename imageTout, typename imageTin>
int	mx::improc::medianSmooth (imageTout &imOut, int &xMax, int &yMax, typename imageTout::Scalar &pMax, const imageTin &imIn, int medianFullWidth)
template<typename imageTout, typename imageTin>
int	mx::improc::medianSmooth (imageTout &imOut, const imageTin &imIn, int medianFullWidth)
	Smooth an image using the median in a rectangular box.
template<typename eigenImT>
void	mx::improc::rowEdgeMedSubtract (eigenImT &im, int ncols)
template<typename eigenImT>
void	mx::improc::colEdgeMedSubtract (eigenImT &im, int nrows)
template<typename vecT, typename eigenImT1, typename eigenImT2, typename eigenImT3>
void	mx::improc::radprof (vecT &rad, vecT &prof, const eigenImT1 &im, const eigenImT2 &radim, const eigenImT3 *mask, bool mean=false, typename eigenImT1::Scalar minr=0)
	Calculate the the radial profile.
template<typename vecT, typename eigenImT1, typename eigenImT2>
void	mx::improc::radprof (vecT &rad, vecT &prof, const eigenImT1 &im, const eigenImT2 &mask, bool mean=false)
	Calculate the the radial profile.
template<typename vecT, typename eigenImT1>
void	mx::improc::radprof (vecT &rad, vecT &prof, const eigenImT1 &im, bool mean=false, double dr=1)
	Calculate the the radial profile.
template<typename radprofT, typename eigenImT1, typename eigenImT2, typename eigenImT3>
void	mx::improc::radprofim (radprofT &radprofIm, eigenImT1 &im, const eigenImT2 &rad, const eigenImT3 *mask, bool subtract, bool mean=false)
	Form a radial profile image, and optionally subtract it from the input.
template<typename radprofT, typename eigenImT>
void	mx::improc::radprofim (radprofT &radprof, eigenImT &im, bool subtract=false, bool mean=false)
	Form a radial profile image, and optionally subtract it from the input.
template<typename eigenImT, typename eigenImT1, typename eigenImT2, typename eigenImT3>
void	mx::improc::stddevImage (eigenImT &stdIm, const eigenImT1 &im, const eigenImT2 &rad, const eigenImT3 &mask, typename eigenImT::Scalar minRad, typename eigenImT::Scalar maxRad, bool divide)
	Form a standard deviation image, and optionally normalize the input relative to the local mean to form a S/N map.
template<typename eigenImT, typename eigenImT1, typename eigenImT2>
void	mx::improc::stddevImage (eigenImT &stdIm, const eigenImT1 &im, const eigenImT2 &mask, typename eigenImT::Scalar minRad, typename eigenImT::Scalar maxRad, bool divide=false)
	Form a standard deviation image, and optionally normalize the input relative to the local mean to form a S/N map.
template<typename eigenCubeT, typename eigenCubeT1, typename eigenCubeT2, typename radT1, typename radT2>
void	mx::improc::stddevImageCube (eigenCubeT &stdImc, const eigenCubeT1 &imc, const eigenCubeT2 &maskCube, radT1 minRad, radT2 maxRad, bool divide=false)

Function Documentation

colEdgeMedSubtract()

template<typename eigenImT>

void mx::improc::colEdgeMedSubtract	(	eigenImT &	im,
		int	nrows )

Parameters

im	The image to filter
nrows	The number of rows on each side of the image to use as the reference

Definition at line 1101 of file imageFilters.hpp.

References mx::math::vectorMedian().

rowEdgeMedSubtract()

template<typename eigenImT>

void mx::improc::rowEdgeMedSubtract	(	eigenImT &	im,
		int	ncols )

Parameters

im	The image to filter
ncols	The number of columns on each side of the image to use as the reference

Definition at line 1074 of file imageFilters.hpp.

References mx::math::vectorMedian().