Take this image of Shia LaBeouf with a green screen behind him from the famous meme where Shia stands in front of a green screen giving a strangely effective motovational speech.

If you haven't seen it, check it out. You'll be glad you did.

Superimpose Shia on the below image of me and friends.

1. Import pillow library or Python Image Library must be used to manipulate images on a pixel level.

2. Each pixel of the image containing the green screen is parsed and compares RGB value with a threshold in order to determine the 'greenness' of the pixel.

3. Once the 'greenness' of the pixel is determined to be a green screen element, replace the pixel with a corresponding pixel from the background image.

4. After this is repeated for all pixels (Shia LaBeouf image is 509x905, which means 460,645 pixels), save the image as a standalone.

5. The threshold is the heart of the algorithm, therefore outputing the RGB values for each pixel from the Shia LaBeouf image into a CSV could provide insight to an improved algorithm.

6. Voilá, we have our final product. I don't seem to have made the final cut but that's okay.

"Don't let your dreams be dreams!" Shia LaBeouf

Notice a green outline on our hero, Shia LaBeouf, in the final image.
Fine tuning the chroma key algorithm to detect a greater range of greens could result in a cleaner image.

os for writing our RGB values to find threshold in foreground image.
pillow or Python Image Library to manipulate images on a pixel level.