mxlib
c++ tools for analyzing astronomical data and other tasks by Jared R. Males. [git repo]
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Image filters (smoothing, radial profiles, etc.) More...
Image filters (smoothing, radial profiles, etc.)
Definition in file imageFilters.hpp.
Go to the source code of this file.
Classes | |
struct | mx::improc::gaussKernel< _arrayT, _kernW > |
Symetric Gaussian smoothing kernel. More... | |
struct | mx::improc::azBoxKernel< _arrayT, _kernW > |
Azimuthally variable boxcare kernel. More... | |
Namespaces | |
mx | |
The mxlib c++ namespace. | |
Functions | |
template<typename imageOutT , typename imageInT , typename kernelT > | |
void | mx::improc::filterImage (imageOutT &fim, imageInT im, kernelT kernel, int maxr=0) |
Filter an image with a mean kernel. More... | |
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. More... | |
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. More... | |
template<typename imageTout , typename imageTin > | |
int | mx::improc::medianSmooth (imageTout &imOut, int &xMax, int &yMax, typename imageTout::Scalar &pMax, const imageTin &imIn, int medianFullWidth) |
Smooth an image using the median in a rectangular box. Also Determines the location and value of the highest pixel in the smoothed image. More... | |
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. More... | |
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. More... | |
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. More... | |
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. More... | |
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. More... | |
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. More... | |
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 divide the input by it to form a S/N map. More... | |
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 divide the input by it to form a S/N map. More... | |
template<typename eigenCubeT , typename eigenCubeT1 , typename eigenImT > | |
void | mx::improc::stddevImageCube (eigenCubeT &stdImc, const eigenCubeT1 &imc, const eigenImT &mask, typename eigenImT::Scalar minRad, typename eigenImT::Scalar maxRad, bool divide=false) |
Form a standard deviation image for each imamge in a cube, and optionally divide the input by it forming a S/N map cube. More... | |
void mx::improc::colEdgeMedSubtract | ( | eigenImT & | im, |
int | nrows | ||
) |
im | The image to filter |
nrows | The number of rows on each side of the image to use as the reference |
Definition at line 760 of file imageFilters.hpp.
References mx::improc::colEdgeMedSubtract().
Referenced by mx::improc::colEdgeMedSubtract().
void mx::improc::rowEdgeMedSubtract | ( | eigenImT & | im, |
int | ncols | ||
) |
im | The image to filter |
ncols | The number of columns on each side of the image to use as the reference |
Definition at line 733 of file imageFilters.hpp.
References mx::improc::rowEdgeMedSubtract().
Referenced by mx::improc::rowEdgeMedSubtract().