When converting an image in OpenCV from color to grayscale, what conversion algorithm is used? I tried to look this up in the source code on GitHub, but I did not have any success.
The lightness method averages the most prominent and least prominent colors:
(max(R, G, B) + min(R, G, B)) / 2.
The average method simply averages the values:
(R + G + B) / 3.
The luminosity method is a more sophisticated version of the average method. It also averages the values, but it forms a weighted average to account for human perception. We’re more sensitive to green than other colors, so green is weighted most heavily.
The formula for luminosity is 0.21 R + 0.72 G + 0.07 B.
Here is an example of some conversion algorithms:
http://www.johndcook.com/blog/2009/08/24/algorithms-convert-color-grayscale/
The color to grayscale algorithm is stated in the cvtColor() documentation. (search for RGB2GRAY).
The formula used is the same as for CCIR 601:
Y = 0.299 R + 0.587 G + 0.114 B
The luminosity formula you gave is for ITU-R Recommendation BT. 709. If you want that you can specify CV_RGB2XYZ
(e.g.) in the third parameter to cvtColor()
then extract the Y channel.
You can get OpenCV to to do the "lightness" method you described by doing a CV_RGB2HLS
conversion then extract the L channel. I don't think that OpenCV has a conversion for the "average" method,
but if you explore the documentation you will see that there are a few other possibilities.
Just wanted to point out that:
img = cv2.imread(rgbImageFileName)
b1 = img[:,:,0] # Gives **Blue**
b2 = img[:,:,1] # Gives Green
b3 = img[:,:,2] # Gives **Red**
On the other hand, loading it as a numeric array works fine:
imgArray= gdalnumeric.LoadFile(rgbImageFileName)
Red = imgArray[0, :, :].astype('float32')
Green = imgArray[1, :, :].astype('float32')
Blue = imgArray[2, :, :].astype('float32')
So just watch out for these oddities.
But when converting to Grayscale cv2.cvtColor uses the the bands correctly.
I compared pixel values using Matlab's rgb2gray.
Cheers