The answer of Helder is correct. I just want to add the fact that Poisson noise is not additive and you can not add it as Gaussian noise.
Depend on what you want to achieve, here is some suggestions:
Simulate a low-light noisy image (if PEAK = 1, it will be really noisy)
import numpy as np
image = read_image("YOUR_IMAGE") # need a rescale to be more realistic
noisy = np.random.poisson(image / 255.0 * PEAK) / PEAK * 255 # noisy image
Add a noise layer on top of the clean image
import numpy as np
image = read_image("YOUR_IMAGE")
noisemap = create_noisemap()
noisy = image + np.random.poisson(noisemap)
Then you can crop the result to 0 - 255 if you like (I use PIL so I use 255 instead of 1).
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