mxlib
c++ tools for analyzing astronomical data and other tasks by Jared R. Males. [git repo]
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Image filtering with a kernel.
Classes | |
struct | mx::improc::gaussKernel< _arrayT, _kernW > |
Symetric Gaussian smoothing kernel. More... | |
struct | mx::improc::azBoxKernel< _arrayT, _kernW > |
Azimuthally variable boxcare kernel. More... | |
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... | |
void mx::improc::filterImage | ( | imageOutT & | fim, |
imageInT | im, | ||
kernelT | kernel, | ||
int | maxr = 0 |
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Filter an image with a mean kernel.
Applies the kernel to each pixel in the image and sums, storing the filtered result in the output image. The kernel-type (kernelT) must have the following interface:
[out] | fim | will be allocated with resize, and on output contains the filtered image |
[in] | im | is the image to be filtered |
[in] | kernel | a fully configured obect of type kernelT |
[in] | maxr | is the maximum radius from the image center to apply the kernel. pixels outside this radius are set to 0. |
imageOutT | the type of the output image (must have an Eigen like interface) |
imageInT | the type of the input image (must have an Eigen like interface) |
kernelT | is the kernel type (see above) |
Definition at line 277 of file imageFilters.hpp.
Referenced by mx::improc::imCenterCircleSym< realT >::center(), and mx::improc::HCIobservation< _realT >::preProcess().