tf.signal.idct

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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/float64 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/float64 Tensor containing the IDCT of input.

Raises:

• ValueError: If type is not 1, 2 or 3, n is not None,axisis not-1, ornormis notNoneor'ortho'`.

Scipy Compatibility

Equivalent to scipy.fftpack.idct for Type-I, Type-II and Type-III DCT.