Color range conversion¶
Some of the docstrings for this module have been extracted from the scikit-image library and are covered by their respective licenses.
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class
node_colors.
ColorRangeConversion
[source]¶ Changes the range and distribution of values for all pixels
Algorithms: -
Improves contrast by stretching and equalizing the histogramin a sliding window over the image
- bins:
Number of bins in computed histogram (default 256)
- adaptive kernel size:
Size of the sliding window. Must evenly divide both image width and height.
- sigma:
Clipping limit (normalized between 0 and 1). Higher values give more contrast. (default 1.0)
-
Applies the correction: Vout = scale Vin^gamma
Processes each channel separately
- scale:
Constant scale factor applied after gamma correction
- gamma:
Gamma factor applied to image.
<1 increases intensities of mid-tones,
>1 decreases intensities of mid-tones
-
Improves contrast by stretching and equalizing the histogram
- bins:
Number of bins in computed histogram (default 256)
-
Applies the correction: Vout = scale log(1 + Vin)
Processes each channel separately
- scale:
Constant scale factor applied after gamma correction
- inverse:
Perform inverse log-correction instead (default false):
Vout = scale (2^Vin - 1)
-
Performs Sigmoid correction on input image. Also known as contrast adjustment.
Vout = 1/(1+exp(gain*(cutoff-Vin)))
Processes each channel separately
- inverse:
Perform negative sigmoid correction instead (default false)
- cutoff:
Shifts the characteristic curve for the sigmoid horizontally(default 0.5)
- gain:
Gain of sigmoid, affects rise time of curve (default 10.0)
Inputs: source : image
source image to filter
Outputs: result : image
result after filtering
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