I'm relatively new to image processing, so I hope I don't ask trivial questions.
I have some images that I want to use in a machine learning context. The images have four color channels: RGB and NIR (near infrared). After some research, it seems like the LAB color space is better suited for machine learning in many cases than the RGB one.
First question would be: is that correct, or did I just fall for single people claiming something?
The second, more important question: Is there a way to properly include NIR in the LAB color space? Or would it be better to keep it as separate information?
And lastly, another question that came up: Can I even transform RGB to LAB properly? What information would I need (wavelengths of red, green and blue; some information on the whitepoint, ...)? Is there a different color space better suited?
If relevant: I am focusing on plant images and tasks appearing there, e.g. plant/background segmentation, fruit detection, leave counting,...