I'm attempting to speed up my genetic algorithm that modifies images. After searching, I've found that my fitness function is the bottleneck, taking sometimes up to 11 seconds to complete. The fitness function compares to images and returns a float. To test, I used some large images of the same size (1254 x 834). What can I do to speed this process up?

def fitness(original, new):
    fitness = 0

    for x in range(0, width):
        for y in range(0, height):
            r1, g1, b1 = original.getpixel((x, y))
            r2, g2, b2 = new.getpixel((x, y))

            deltaRed = abs(r1 - r2)
            deltaGreen = abs(g1 - g2)
            deltaBlue = abs(b1 - b2)

            pixelFitness = pixelFitness = math.sqrt(deltaRed ** 2 + deltaGreen ** 2 + deltaBlue ** 2)

            fitness += pixelFitness

    return fitness

I'm attempting to speed up my genetic algorithm that modifies images. After searching, I've found that my fitness function is the bottleneck, taking sometimes up to 11 seconds to complete. 

The fitness function accepts two images and returns a float representing the total difference between the images' corresponding pixels, measured as distance in Cartesian RGB space. 

To test, I used some large images of the same size (1254 x 834). What can I do to speed this process up?

def fitness(original, new):
    fitness = 0

    for x in range(0, width):
        for y in range(0, height):
            r1, g1, b1 = original.getpixel((x, y))
            r2, g2, b2 = new.getpixel((x, y))

            deltaRed = abs(r1 - r2)
            deltaGreen = abs(g1 - g2)
            deltaBlue = abs(b1 - b2)

            pixelFitness = pixelFitness = math.sqrt(deltaRed ** 2 + deltaGreen ** 2 + deltaBlue ** 2)

            fitness += pixelFitness

    return fitness