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.

class node_colors.ColorRangeConversion

Changes the range and distribution of values for all pixels

Algorithms:

• adaptive histogram

  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)

• gamma correction

  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

• histogram equalization

  Improves contrast by stretching and equalizing the histogram

  bins:

  Number of bins in computed histogram (default 256)

• log correction

  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)

• sigmoid

  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