Adding poisson noise to an image

Question

I have some images that I need to add incremental amounts of Poisson noise to in order to more thoroughly analyze them. I know you can do this in MATLAB, but how do you go about doing it in Python? Searches have yielded nothing so far.

Answer 1

Actually the answer of Paul doesnt make sense.

Poisson noise is signal dependent! And using those commands, provided by him, the noise later added to the image is not signal dependent.

To make it signal dependent you shold pass the image to the NumPy's poisson function:

filename = 'myimage.png'
img = (scipy.misc.imread(filename)).astype(float)

noise_mask = numpy.random.poisson(img)

noisy_img = img + noise_mask

Answer 2

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).