How to scale numpy array (image) values to a certain range quickly, without changing the image in an-CodePudding

I have a numpy array H_arr representing the following image:

(IMG 1)

and I wish to convert its values in the range [0,1], let's call this new array as New_arr, in such a way that the original image remains intact. What I mean is that the exact same image (IMG 1) should be displayed when I use plt.imshow(New_arr).

The data type of H_arr is float32, with H_arr.min() giving -24.198463 and H_arr.max() giving 26.153196. H_arr.shape gives (960, 1280, 3).

I had earlier thought that I would use the following formula to convert it to the 0-1 range:

newvalue= (new_max-new_min)/(max-min)*(value-max) new_max

and implement it as:

New = np.zeros((H_arr.shape[0],H_arr.shape[1],H_arr.shape[2]),dtype = float)
for i in range(H_arr.shape[0]):
  for j in range(H_arr.shape[1]):
    for k in range(H_arr.shape[2]):
      New[i][j][k]= (1-0)/(H_arr.max()-H_arr.min())*(H_arr[i][j][k]-H_arr.max()) 1

But this is computationally quite expensive. Any input on how I should go about converting the original array is appreciated.

Edit: After incorporating the answers below, I can do it quite quickly within the [0,1] range, but the image drastically changes to

How do I make sure that my image remains the same as before?

CodePudding user response：

You can apply your formular to the entire array at once. No loop required, just remove the indices:

New= (1-0)/(H_arr.max()-H_arr.min())*(H_arr-H_arr.max()) 1

CodePudding user response：

You can go directly without loops

import numpy as np

shape = 256, 256, 3
vmin, vmax = -24.198463, 26.153196

arr = np.random.rand(*shape) * (vmax - vmin)   vmin

# Actual vmin and vmax, due to random
vmin, vmax = arr.min(), arr.max()

# Scaling in [0, 1]
scaled_01 = (arr - vmin) / (vmax - vmin)

print(f"{scaled_01.min() = }")
print(f"{scaled_01.max() = }")

# Scaling into new [vmin, vmax]
vmin_new, vmax_new = 10, 34
scaled = ((arr - vmin) / (vmax - vmin)) * (vmax_new - vmin_new)   vmin_new

print(f"{scaled.min() = }")
print(f"{scaled.max() = }")

scaled_01.min() = 0.0
scaled_01.max() = 1.0
scaled.min() = 10.0
scaled.max() = 34.0