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Range Normalization

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Range (min-max) normalization for image patches.

RangeNormalization

Bases: Normalization

Normalize an image or image patch to [0, 1] range.

This transform expects C(Z)YX dimensions for normalization and BC(Z)YX for denormalization. Returns float32 arrays.

Parameters:

  • input_mins (list of float) –

    Minimum value per channel.

  • input_maxes (list of float) –

    Maximum value per channel.

  • target_mins (list of float, default: None ) –

    Target minimum value per channel.

  • target_maxes (list of float, default: None ) –

    Target maximum value per channel.

  • skip_target (bool, default: False ) –

    When True, target normalization is skipped and the target is returned unchanged.

Attributes:

  • input_mins (list of float) –

    Minimum value per channel.

  • input_maxes (list of float) –

    Maximum value per channel.

  • target_mins (list of float, optional) –

    Target minimum value per channel.

  • target_maxes (list of float, optional) –

    Target maximum value per channel.

  • skip_target (bool) –

    When True, target normalization is skipped and the target is returned unchanged.

__call__(patch, target=None)

Apply range normalization to patch and optional target.

Parameters:

  • patch (NDArray) –

    Patch with shape C(Z)YX.

  • target (NDArray, default: None ) –

    Target patch with shape C(Z)YX.

Returns:

  • tuple of NDArray –

    Normalized patch and target (target can be None).

__init__(input_mins, input_maxes, target_mins=None, target_maxes=None, skip_target=False)

Initialize range normalization.

Parameters:

  • input_mins (list of float) –

    Minimum value per channel.

  • input_maxes (list of float) –

    Maximum value per channel.

  • target_mins (list of float or None, default: None ) –

    Target minimum per channel.

  • target_maxes (list of float or None, default: None ) –

    Target maximum per channel.

  • skip_target (bool, default: False ) –

    When True, target normalization is skipped and the target is returned unchanged (as float32). Default is False.

denormalize(patch)

Reverse the normalization operation for a batch of patches.

The data is denormalized using the target range, when available. When no target range is available, which is the case for self-supervised algorithms such as N2V, the data is denormalized using the input range.

If self.skip_target is True, then this method returns patch.

Parameters:

  • patch (Tensor) –

    Normalized patch with shape BC(Z)YX.

Returns:

  • Tensor –

    Denormalized patch.