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| genre | LUT |
| status | stable |
| author | Mathias Schlueter |
| package | MeVisLab/Standard |
| dll | MLTransferFunction |
| definition | MLTransferFunction.def |
| see also | TransferFunction |
| keywords | Transfer, function, gradation, gamma, lut, window, scale |
The module Gradation transforms the image at the first image input to an output image using a transfer function object which can be selected for example by the TransferFunction module.
The transformation can be selectively applied by connecting a mask image to the second image input.
Then, the mask value at an image position defines the fraction of the transfer function applied to the first image.
Connect a transfer function object to the input inputTransferFunction and an input image to the first image input.
Then the output image is the input image transformed by the transfer function object.
Optionally, connect a mask image to the second image input. Then the first input image is transformed paritally according to the mask values.
The domain of the image values [min,max] is scaled to [0,1] before applying the transfer function.
The output of the transfer function is then rescaled to the original domain of the image. Thus data types and min/max - values of the input- and output image are equal.
When a mask image is connected to the second image input, the value of the output image at some position is a linear combination of the input value and the transformed input value with weighting coefficients defined by the mask value at the position.
If the mask value is less or equal to the minimum value of the mask image no transformation is applied.
If mask value is greater or equal to the maximum value of the mask image the transformation is competely applied.
The image extensions and the data types of the two input images have to be equal.
Otherwise the output image is invalidated.