Hi, I have a silly question. Is the following class the right normalization for 3D grayscale images?

```
def __init__(self):
pass
def __call__(self,vol):
vol = vol-vol.mean()/vol.std()
return(vol) ```
If so, should I expect after applying this nor,alization the mean of transformed image ill be zero and std will be one?
```

You should wrap the subtraction into parentheses, otherwise you would scale the `mean`

value by the inverse `std`

.

If thatâ€™s fixed, your output should have a zero mean (or something around `1e-6`

) and a unit variance.

It was solved. Thank you @ptrblck. The variance also is near 1, not exactly 1, is that true?

How large is the difference between the calculated variance and the theoretical `1.`

?

This is mean `1.3271347e-07`

and this is std `0.9999998`

.

This seems to be alright, as the difference is in the floating point precision limits.

Thank you for your answer.