adding noise to an array. Is it addition or multiplication?
It depends what sort of physical model you are trying to represent; additive and multiplicative noise do not correspond to the same phenomenon. Your image can be considered a variable that changes through time. Noise is an extra term that varies randomly as time passes. If this noise term depends on the state of the image in time, then the image and the noise are correlated and noise is multiplicative. If the two terms are uncorrelated, noise is additive.
I have some code that just makes some random noise using the numpy random normal distribution function and then I add this to a numpy array that contains an image of my chosen object. I then have to clip the array to between values of -1 and 1.
I am just trying to get my head round whether I should be adding this to the array and clipping or multiplying the array by the noise and clipping?
I can't conceptually understand which I should be doing. Could someone please help?
Thanks