adding noise to an array. Is it addition or multiplication?
Well as you have said it yourself, the problem is that you don't know what you want.
Both methods will increase the entropy of the original data.
What is the purpose of your task?
If you want to simulate something like sensor noise, the addition will do just fine.
You can try both and observe what happens to the distribution of your original data set after the application.
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