MATLAB: Greenness of an RGB image

Image Processing Toolboxrgb

Hi,

in an other thread I found this equation to compute the "greenness" of an RGB image:

greenDifference = abs(greenChannel – (redChannel + blueChannel)/2);

Look here: http://www.mathworks.de/matlabcentral/answers/38571

Can anybody name a literature source for this equation? I desperately need a source for my master thesis.

Thanks for your help.

Best Answer

As Image Analyst has said, it is just something well known and logical. Thus a high green component makes for a greenish color. A low value for (red + blue) also makes for green-ness. Is this exact? Not really, merely a good measure that will correlate with perceived green-ness.

I would suggest that someone made a rather large mistake when they formulated that expression. (Assuming RGB is scaled over the range [0,255].) The color [0 255 0] is a green. However, this formula, because of the abs, would also call [255 0 255] a greenish color, when clearly that is not at all green, in fact, a deep purple, so anti-green.

A better expression would arguably be to remove the abs:

greenDifference = greenChannel - (redChannel + blueChannel)/2;

Here green-ness can go negative, in fact we could have a green-ness measure that varies over the range [-255,255], with 255 as the maximum green-ness, and -255 as a maximal anti-green.

(If your image is scaled [0,1], then the green-ness measure here would vary from -1 to 1.)

If you preferred a measure that is scaled on the interval [0,255], then a good measure would be to transform it as:

greenDifference = (255 + greenChannel - (redChannel + blueChannel)/2)/2;

A similar version would work for images scaled over [0,1].

And finally, if your numbers are uint8, then you need to beware overflows and underflows. So you might convert first to int16 (or even a floating point representation) to avoid those failures.

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Try this:

% Extract the individual red, green, and blue color channels.
redChannel = rgbImage(:, :, 1);
greenChannel = rgbImage(:, :, 2);
blueChannel = rgbImage(:, :, 3);
% Now swap around in any way you want.
newRedChannel = greenChannel;
newGreenChannel = blueChannel; 
newBlueChannel = redChannel;
% Recombine separate color channels into a single, true color RGB image.
NewRgbImage = cat(3, newRedChannel, newGreenChannel, newBlueChannel);

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I think you're confused. But here is your first paragraph:

% gets an RGB image, 
rgbImage = imread('peppers.png'); % Read in sample demo image.
% transforms it to grayscale 
grayImage = rgb2gray(rgbImage);
% then extracts its red and green channel. 
redChannel = rgbImage(:, :, 1); % Extract red channel.
greenChannel = rgbImage(:, :, 2); % Extract green channel.
% I need to get the same image, convert it to Cielab color space 
labImage = rgb2lab(rgbImage);
% and then transform it to grayscale and then extract the red and green channels too.
% We already did that -- just use grayImage, redChannel, and greenChannel.

Now, for your second paragraph:

1) Is the L "channel" the CieLab image already in grayscale or should I perform something else to get it?

The L channel is a monochrome, single valued image that represents the lightness of the image. You can consider it gray scale, just like you can with redChannel or greenChannel or grayImage.

2) Is it possible to get separated red and green channels from A "channel" as I got from the image in RGB color space?

No. The A channel is also a monochrome channel and it has no red and green channels. The A channel represents the redness to greenness of the color. But the A channel is not a color image. Neither is the L channel or B channel. They're monochrome. And the labImage is not a "true color" image, as in an RGB image, so if you display it with imshow, which expects an RGB image, it will look weird. It will display the L image as red, the A image as green, and the B image as blue and the whole image will look bizarre. The lab image is not meant to be displayed. It's meant to allow for color segmentation or to measure color differences.

And to make it more confusing, the lab image you get from rgb2lab() or applycform() does not give the lab colors you'd get from your colorimeter or spectrophotometer, but that's a whole other discussion.

Best Answer

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