Fast Discrete Shearlet Transform layers in TensorFlow
Project description
TFDST: Fast Discrete Shearlet Transform Layers in TensorFlow
TFDST provides differentiable TensorFlow/Keras layers for fast 2D and 3D
discrete shearlet transforms and their inverse transforms.
Copyright 2025 Kishore Kumar Tarafdar. Filter-bank construction follows mathematical structure developed with credit to Vineet Ghule. This implementation provides differentiable TensorFlow/Keras layers with batched multichannel support and performance-oriented updates.
Capabilities
DST2D/IDST2Dthroughtransform=Noneortransform="inverse"DST3D/IDST3Dthroughtransform=Noneortransform="inverse"- Batched multichannel TensorFlow tensors
- Backpropagation through the transform layers
Limitations
- Inputs are expected to match the configured spatial size
N. - 2D input shape:
[batch, N, N, channels]. - 3D input shape:
[batch, N, N, N, channels]. - Wavelet filter coefficients are provided through
PyWavelets.
Installation
pip install TFDST
Minimal Example
import tensorflow as tf
from TFDST.DST2DFB import DST2D
from TFDST.DST3DFB import DST3D
N = 32
# 2D
x2 = tf.random.normal([1, N, N, 1])
dst2 = DST2D(N=N, J=2, L=[1, 2], B=[4, 8], norm=True, wave="bior1.5")
idst2 = DST2D(N=N, J=2, L=[1, 2], B=[4, 8], norm=True, wave="bior1.5", transform="inverse")
y2 = dst2(x2)
r2 = idst2(y2)
# 3D
x3 = tf.random.normal([1, N, N, N, 1])
dst3 = DST3D(N=N, J=2, L=[1, 2], B=[4, 8], norm=True, wave="bior1.5")
idst3 = DST3D(N=N, J=2, L=[1, 2], B=[4, 8], norm=True, wave="bior1.5", transform="inverse")
y3 = dst3(x3)
r3 = idst3(y3)
print(x2.shape, r2.shape)
print(x3.shape, r3.shape)
Arguments
| Argument | Meaning |
|---|---|
N |
Spatial size of each axis; 2D uses N x N, 3D uses N x N x N. |
J |
Number of multiscale shearlet levels. |
L |
Shear parameters per level; must have length J. |
B |
Bandwidth/window parameters per level; must have length J. |
wave |
PyWavelets wavelet name used for the radial wavelet filters, e.g. "bior1.5". |
norm |
If True, applies filter-bank normalization. |
transform |
Use None for forward DST and "inverse" for inverse DST. |
License
Apache License 2.0. See LICENSE.
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