Save numpy array as image with high precision (16 bits) with scikit-image

Question

I am working with 2D floating-point numpy arrays that I would like to save to greyscale .png files with high precision (e.g. 16 bits). I would like to do this using the scik

Answer 1

You wanna use the freeimage library to do so:

import numpy as np
from skimage import io, exposure, img_as_uint, img_as_float

io.use_plugin('freeimage')

im = np.array([[1., 2.], [3., 4.]], dtype='float64')
im = exposure.rescale_intensity(im, out_range='float')
im = img_as_uint(im)

io.imsave('test_16bit.png', im)
im2 = io.imread('test_16bit.png')

Result:

[[    0 21845]
 [43690 65535]]

As for 3D arrays, you need to construct the array properly and then it'll work:

# im = np.array([[1, 2.], [3., 4.]], dtype='float64')
im = np.linspace(0, 1., 300).reshape(10, 10, 3)
im = exposure.rescale_intensity(im, out_range='float')
im = img_as_uint(im)

io.imsave('test_16bit.png', im)
im2 = io.imread('test_16bit.png')

Note that the read image is flipped, so something like np.fliplr(np.flipud(im2)) will bring it to original shape.