Colorfulness analysis¶
This module contains function to evaluate the colorfulness of an image in both the HSV and RGB color spaces.
@author: Giulio Gabrieli
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colorfulness.
colorfulnessHSV
(img)¶ This function evaluates the colorfulness of a picture using the formula described in Yendrikhovskij et al., 1998. Input image is first converted to the HSV color space, then the S values are selected. Ci is evaluated with a sum of the mean S and its std, as in:
Ci = mean(Si)+ std(Si)
Parameters: img (numpy.ndarray) – image to analyze, in RGB Returns: colorfulness index Return type: float
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colorfulness.
colorfulnessRGB
(img)¶ This function evaluates the colorfulness of a picture using Metric 3 described in Hasler & Suesstrunk, 2003. Ci is evaluated with as:
Ci =std(rgyb) + 0.3 mean(rgyb) [Equation Y] std(rgyb) = sqrt(std(rg)^2+std(yb)^2) mean(rgyb) = sqrt(mean(rg)^2+mean(yb)^2) rg = R - G yb = 0.5(R+G) - B
Parameters: img (numpy.ndarray) – image to analyze, in RGB Returns: colorfulness index Return type: float
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colorfulness.
sRGB2RGB
(img)¶ this function converts a sRGB img to linear RGB values.
Parameters: img (numpy.ndarray) – image to analyze, in sRGB Returns: image to analyze, in RGB Rtyipe: numpy.ndarray