template<typename
PixelT>
class lsst::ip::diffim::detail::KernelPcaVisitor< PixelT >
A class to run a PCA on all candidate kernels (represented as Images).
- Note
- Templated on the pixel types of the MaskedImages it will be visiting (typically float).
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Works in concert with a afwMath::SpatialCellSet and ip::Diffim KernelPca to create a Karhunen-Loeve basis from all the good KernelCandidates. This class adds the extra functionality to subtract off the mean kernel from all entries, which makes the resulting basis more compact. The user needs to manually add this mean image into the resulting basis list after imagePca.analyze() is called.
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KernelPca (and base class afwImage::ImagePca) weight objects of different brightness differently. However we don't necessarily want images with larger kernel sums to have more weight. Each kernel should have constant weight in the Pca. For simplicity we scale them to have the same kernel sum, 1.0, and send to ImagePca that the flux (weight) is 1.0.
Definition at line 40 of file KernelPca.h.