Should I consider rgb values of a pixel as one value? I was reading this paper for a project work.


  We train on 1.6 million 32*32 color images that have been preprocessed
  by subtracting from each pixel its mean value over all images and then
  dividing by the standard deviation of all pixels over all images.


I've trouble distinguishing between "from each pixel its mean value over all images" and "standard deviation of all pixels over all images". 

Since, I'm dealing with color images, can I just take rgb values of each pixel as one value or should I calculate the mean and SD for every color differently?

For example if I have r=255, g=255, b=255, can I take pixel value as (in binary), (r&lt;&lt;16)+(g&lt;&lt;8)+b ?
For example if I have r=255, g=255, b=255, can I take pixel value as (in binary), (r&lt;&lt;16)+(g&lt;&lt;8)+b ?


While this number would identify the colour, it would not help with a mean or standard deviation. e.g. pure blue would be 255 but pure red would be 16711680

The paper is unclear so you have a few choices:


Process each channel individually
Convert the image to grayscale, find the mean and std dev, and use this for each channel.


There may be other methods that use different colour spaces.