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Spectral Distortion Index

Module Interface

class torchmetrics.SpectralDistortionIndex(p=1, reduction='elementwise_mean', **kwargs)[source]

Compute Spectral Distortion Index (SpectralDistortionIndex) also now as D_lambda is used to compare the spectral distortion between two images.

As input to forward and update the metric accepts the following input

  • preds (Tensor): Low resolution multispectral image of shape (N,C,H,W)

  • target``(:class:`~torch.Tensor`): High resolution fused image of shape ``(N,C,H,W)

As output of forward and compute the metric returns the following output

  • sdi (Tensor): if reduction!='none' returns float scalar tensor with average SDI value over sample else returns tensor of shape (N,) with SDI values per sample

Parameters
  • p (int) – Large spectral differences

  • reduction (Literal[‘elementwise_mean’, ‘sum’, ‘none’]) –

    a method to reduce metric score over labels.

    • 'elementwise_mean': takes the mean (default)

    • 'sum': takes the sum

    • 'none': no reduction will be applied

  • kwargs (Any) – Additional keyword arguments, see Advanced metric settings for more info.

Example

>>> import torch
>>> _ = torch.manual_seed(42)
>>> from torchmetrics import SpectralDistortionIndex
>>> preds = torch.rand([16, 3, 16, 16])
>>> target = torch.rand([16, 3, 16, 16])
>>> sdi = SpectralDistortionIndex()
>>> sdi(preds, target)
tensor(0.0234)

Initializes internal Module state, shared by both nn.Module and ScriptModule.

Functional Interface

torchmetrics.functional.spectral_distortion_index(preds, target, p=1, reduction='elementwise_mean')[source]

Calculate Spectral Distortion Index (SpectralDistortionIndex) also known as D_lambda that is used to compare the spectral distortion between two images.

Parameters
  • preds (Tensor) – Low resolution multispectral image

  • target (Tensor) – High resolution fused image

  • p (int) – Large spectral differences

  • reduction (Literal[‘elementwise_mean’, ‘sum’, ‘none’]) –

    a method to reduce metric score over labels.

    • 'elementwise_mean': takes the mean (default)

    • 'sum': takes the sum

    • 'none': no reduction will be applied

Return type

Tensor

Returns

Tensor with SpectralDistortionIndex score

Raises
  • TypeError – If preds and target don’t have the same data type.

  • ValueError – If preds and target don’t have BxCxHxW shape.

  • ValueError – If p is not a positive integer.

Example

>>> from torchmetrics.functional import spectral_distortion_index
>>> _ = torch.manual_seed(42)
>>> preds = torch.rand([16, 3, 16, 16])
>>> target = torch.rand([16, 3, 16, 16])
>>> spectral_distortion_index(preds, target)
tensor(0.0234)
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