tf.signal.idct

TensorFlow 2 version View source on GitHub

Computes the 1D Inverse Discrete Cosine Transform (DCT) of input.

Aliases:

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.

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.