Adjusting contrast of image purely with numpy

Question

I am trying write a contrast adjustment for images in gray scale colors but couldn\'t find the right way to do it so far. This is what I came up with:

import nu         


        

Answer 1

I'm learning Python and numpy and thought I'd try to implement a "LookUp Table" (LUT). It works, and the output image has the full range from black to white, but I'm happy to receive suggestions for improvement.

#!/usr/local/bin/python3
import numpy as np
from PIL import Image

# Open the input image as numpy array, convert to greyscale and drop alpha
npImage=np.array(Image.open("cartoon.png").convert("L"))

# Get brightness range - i.e. darkest and lightest pixels
min=np.min(npImage)        # result=144
max=np.max(npImage)        # result=216

# Make a LUT (Look-Up Table) to translate image values
LUT=np.zeros(256,dtype=np.uint8)
LUT[min:max+1]=np.linspace(start=0,stop=255,num=(max-min)+1,endpoint=True,dtype=np.uint8)

# Apply LUT and save resulting image
Image.fromarray(LUT[npImage]).save('result.png')

Keywords: Python, Numpy, PIL, Pillow, image, image processing, LUT, Look-Up Table, Lookup, contrast, stretch.