Shortcuts

Spectral Distortion Index

Module Interface

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

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

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)

References

[1] Alparone, Luciano & Aiazzi, Bruno & Baronti, Stefano & Garzelli, Andrea & Nencini, Filippo & Selva, Massimo. (2008). Multispectral and Panchromatic Data Fusion Assessment Without Reference. ASPRS Journal of Photogrammetric Engineering and Remote Sensing. 74. 193-200. 10.14358/PERS.74.2.193.

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

compute()[source]

Computes and returns spectral distortion index.

Return type

Tensor

update(preds, target)[source]

Update state with preds and target.

Parameters
  • preds (Tensor) – Low resolution multispectral image

  • target (Tensor) – High resolution fused image

Return type

None

Functional Interface

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

Spectral Distortion Index (SpectralDistortionIndex) also now as D_lambda 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)
Read the Docs v: v0.8.2
Versions
latest
stable
v0.8.2
v0.8.1
v0.8.0
v0.7.3
v0.7.2
v0.7.1
v0.7.0
v0.6.2
v0.6.1
v0.6.0
v0.5.1
v0.5.0
v0.4.1
v0.4.0
v0.3.2
v0.3.1
v0.3.0
v0.2.0
v0.1.0
Downloads
On Read the Docs
Project Home
Builds

Free document hosting provided by Read the Docs.