NormalizeImage
Rescales an image linearly, so that its minimum becomes inNewMinimum and the maximum of the remaining pixels becomes inNewMaximum.
Applications:Aims at better using the image's dynamic range to represent an interesting subset of pixel values.
Syntax
C++
Python
def NormalizeImage( inImage: Image, outImage: Image, /, *, inRoi: Region | None = None, inNewMinimum: float = 0.0, inNewMaximum: float = 255.0, inSaturateBrightestFraction: float = 0.0, inSaturateDarkestFraction: float = 0.0, inMinValue: float | None = None, inMaxValue: float | None = None, diagLinearNormalizedRegion: Region | None = None ) -> ( outA: float, outB: float )
Parameters
| Name | Type | Range | Default | Description | |
|---|---|---|---|---|---|
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inImage | Image | Input image | ||
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inRoi | Region | None | None | Range of pixels to be processed | |
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inNewMinimum | float | 0.0 | Desired minimum value of the resulting image | |
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inNewMaximum | float | 255.0 | Desired maximum value of the resulting image | |
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inSaturateBrightestFraction | float | 0.0 - 1.0 | 0.0 | Fraction of the brightest pixels skipped during normalization |
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inSaturateDarkestFraction | float | 0.0 - 1.0 | 0.0 | Fraction of the darkest pixels skipped during normalization |
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inMinValue | float | None | None | Pixels darker than that value will be skipped during normalization | |
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inMaxValue | float | None | None | Pixels brighter than that value will be skipped during normalization | |
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outImage | Image | Rescaled image | ||
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outA | float | Multiplicative parameter of the applied linear transformation of pixel values | ||
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outB | float | Additive parameter of the applied linear transformation of pixel values | ||
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diagLinearNormalizedRegion | Region | None | None | Region of image that has been linearly normalized |



