Shearlet Transform¶
- class torch_radon.shearlet.ShearletTransform(width, height, alphas, cache=None)[source]¶
Implementation of Alpha-Shearlet transform based on https://github.com/dedale-fet/alpha-transform/tree/master/alpha_transform.
Once the shearlet spectrograms are computed all the computations are done on the GPU.
- Parameters
width – Width of the images
height – Height of the images
alphas – List of alpha coefficients that will be used to generate shearlets
cache – If specified it should be a path to a directory that will be used to cache shearlet coefficients in order to avoid recomputing them at each instantiation of this class.
Note
Support both float and double precision.
- forward(self, x)¶
Do shearlet transform of a batch of images.
- Parameters
x – PyTorch GPU tensor with shape \((d_1, \dots, d_n, h, w)\).
- Returns
PyTorch GPU tensor containing shearlet coefficients. Has shape \((d_1, \dots, d_n, \text{n_shearlets}, h, w)\).
- backward(self, cs)¶
Do inverse shearlet transform.
- Parameters
cs – PyTorch GPU tensor containing shearlet coefficients, with shape \((d_1, \dots, d_n, \text{n_shearlets}, h, w)\).
- Returns
PyTorch GPU tensor containing reconstructed images. Has shape \((d_1, \dots, d_n, h, w)\).