@jhlegarreta raised in #56 that the current StructureTensor name is misleading.
It is a filter that computes a Structure Tensor per pixel but also computes the eigensystem of the tensor. It outputs a matrix with the eigenvectors and eigenvalues per pixel
We should:
[ ] Rename it to someting involving ImageFilter: itkStructureTensorEigenSystemImageFilter maybe?
[ ] Refactor out of the current filter the computation of the StructureTensor. The new class, named correctly itkStructureTensor, will only compute the tensor.
For more info about the tensor:
StructureTensor in wikipedia. The input there is a function I, they calculate its gradient, and do a eigensystem analysis. Here is the same framework but the input is instead a vector of images, not a function (could be a vector with directional derivatives --the gradient--, or the Riesz responses, or any other directional measurements).
In the current ImageFilter we do this calculation for every pixel, and could be slow for large number of inputs, see #61.
@jhlegarreta raised in #56 that the current StructureTensor name is misleading.
It is a filter that computes a Structure Tensor per pixel but also computes the eigensystem of the tensor. It outputs a matrix with the eigenvectors and eigenvalues per pixel
We should:
[ ] Rename it to someting involving ImageFilter:
itkStructureTensorEigenSystemImageFiltermaybe?[ ] Refactor out of the current filter the computation of the StructureTensor. The new class, named correctly
itkStructureTensor, will only compute the tensor.For more info about the tensor: StructureTensor in wikipedia. The input there is a function I, they calculate its gradient, and do a eigensystem analysis. Here is the same framework but the input is instead a vector of images, not a function (could be a vector with directional derivatives --the gradient--, or the Riesz responses, or any other directional measurements).
In the current ImageFilter we do this calculation for every pixel, and could be slow for large number of inputs, see #61.