cutcutcodec.core.analysis.video.complexity.dct.compute_dct¶

cutcutcodec.core.analysis.video.complexity.dct.compute_dct(tensor: Tensor, dim: int) → Tensor[source]¶

Compute the DCT-II on the given axis.

The output vector \(\hat x_k\) is defined as \(\hat x_k = \sum\limits_{l=0}^{n-1} x_l \cos\left(\frac{\pi}{n}\left(l+\frac{1}{2}\right)k\right)\).

It is calculated by a matrix product, computed by dct_matrix().

Parameters¶

inputtorch.Tensor: A n-dimensional tensor of real.
dimint: The axis along which the DCT is computed. The other axes are treated as batch dimensions.

Returns¶

outputtorch.Tensor: The dimension of the input tensor. The input and output have the same size.

Examples¶

>>> import torch
>>> from cutcutcodec.core.analysis.video.complexity.dct import compute_dct
>>> src = torch.randn((128, 16, 16))
>>> 2d_dct = compute_dct(compute_dct(src, -1), -2)  # compute the 2d dct
>>>