TensorFlow 2 version
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View source on GitHub
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Computes the 1D Inverse Discrete Cosine Transform (DCT) of input.
tf.signal.idct(
input, type=2, n=None, axis=-1, norm=None, name=None
)
Currently only Types I, II and III are supported. Type III is the inverse of Type II, and vice versa.
Note that you must re-normalize by 1/(2n) to obtain an inverse if norm is
not 'ortho'. That is:
signal == idct(dct(signal)) * 0.5 / signal.shape[-1].
When norm='ortho', we have:
signal == idct(dct(signal, norm='ortho'), norm='ortho').
Args | |
|---|---|
input
|
A [..., samples] float32 Tensor containing the signals to take
the DCT of.
|
type
|
The IDCT type to perform. Must be 1, 2 or 3. |
n
|
For future expansion. The length of the transform. Must be None.
|
axis
|
For future expansion. The axis to compute the DCT along. Must be -1.
|
norm
|
The normalization to apply. None for no normalization or 'ortho'
for orthonormal normalization.
|
name
|
An optional name for the operation. |
Returns | |
|---|---|
A [..., samples] float32 Tensor containing the IDCT of input.
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Raises | |
|---|---|
ValueError
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If type is not 1, 2 or 3, n is not None,axisis
not-1, ornormis notNoneor'ortho'`.
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Scipy Compatibility
Equivalent to scipy.fftpack.idct for Type-I, Type-II and Type-III DCT.