Synopse

Normalize the pixels values between the specified range.

• g = ianormalize(f, range)
• g: Output: ndmage, same type as f.
• f: Input: ndimage.
• range: Image. vector: minimum and maximum values in the output image, respectively.

Description

Normalize the input image f. The minimum value of f is assigned to the minimum desired value and the maximum value of f, to the maximum desired value. The minimum and maximum desired values are given by the parameter range. The data type of the normalized image is the same data type of input image.

```01. from numpy import *
02.
03. def ianormalize(f, range=[0,255]):
04.
05.     f = asarray(f)
06.     range = asarray(range)
07.     if f.dtype.char in ['D', 'F']:
08.         raise Exception, 'error: cannot normalize complex data'
09.     faux = ravel(f).astype(float)
10.     minimum = faux.min()
11.     maximum = faux.max()
12.     lower = range[0]
13.     upper = range[1]
14.     if upper == lower:
15.         g = ones(f.shape) * maximum
16.     if minimum == maximum:
17.         g = ones(f.shape) * (upper + lower) / 2.
18.     else:
19.         g = (faux-minimum)*(upper-lower) / (maximum-minimum) + lower
20.     g = reshape(g, f.shape)
21.
22.     if f.dtype == uint8:
23.         if upper > 255:
24.             raise Exception,'ianormalize: warning, upper valuer larger than 255. Cannot fit in uint8 image'
25.     g = g.astype(f.dtype) # set data type of result the same as the input image
26.     return g```

Examples

Example 1

```01. from ia636 import ianormalize
02.
03. f = array([100., 500., 1000.])
04. g1 = ianormalize(f, [0,255])
05. print g1
06. g2 = ianormalize(f, [-1,1])
07. print g2
08. g3 = ianormalize(f, [0,1])
09. print g3
10. #
11. f = array([-100., 0., 100.])
12. g4 = ianormalize(f, [0,255])
13. print g4
14. g5 = ianormalize(f, [-1,1])
15. print g5
16. g6 = ianormalize(f, [-0.5,0.5])
17. print g6
18. #
19. f = arange(10).astype('uint8')
20. g7 = ianormalize(f)
21. print g7
22. #
23. f = array([1,1,1])
24. g8 = ianormalize(f)
25. print g8```
```[   0.          113.33333333  255.        ]
[-1.         -0.11111111  1.        ]
[ 0.          0.44444444  1.        ]
[   0.   127.5  255. ]
[-1.  0.  1.]
[-0.5  0.   0.5]
[  0  28  56  85 113 141 170 198 226 255]
[127 127 127]
```