Adjust contrast and save RGB images#

This example shows how to adjust the contrast and intensities using scikit-image and save it as an RGB image.

When saving an RGB image to jpg, only 8 bits are supported and the image intensity needs to be rescaled to 0-255 before converting to 8 bits, otherwise, the intensities will be cropped at the value of 255.

import hyperspy.api as hs
import numpy as np
import skimage as ski

Adjust contrast#

In hyperspy, color images are defined as Signal1D with the signal dimension corresponding to the color channel (red, green and blue)

# The dtype can be changed to a custom dtype, which is convenient to visualise
# the color image
s = hs.signals.Signal1D(ski.data.astronaut())
s.change_dtype("rgb8")
print(s)
<Signal2D, title: , dimensions: (|512, 512)>

Display the color image

s.plot()
Signal

Processing is usually performed on standard dtype (e.g. uint8, uint16), because most functions from scikit-image, numpy, scipy, etc. only support standard dtype. Convert from RGB to unsigned integer 16 bits

s.change_dtype("uint8")
print(s)
  • convert color image
  • Signal
<Signal1D, title: , dimensions: (512, 512|3)>

Adjust contrast (gamma correction)

s.data = ski.exposure.adjust_gamma(s.data, gamma=0.2)

Save to jpg#

Change dtype back to custom dtype rgb8

s.change_dtype("rgb8")
Signal

Save as jpg

s.save("rgb8_image.jpg", overwrite=True)

Save rgb16 image to jpg#

The last part of this example shows how to save rgb16 to a jpg file

Create a signal with rgb16 dtype

s2 = hs.signals.Signal1D(ski.data.astronaut().astype("uint16") * 100)

To save a color image to jpg, the signal needs to be converted to rgb8 because jpg only support 8-bit RGB Rescale intensity to fit the unsigned integer 8 bits (2**8 = 256 intensity level)

s2.data = ski.exposure.rescale_intensity(s2.data, out_range=(0, 255))

Now that the values have been rescaled to the 0-255 range, we can convert the data type to unsigned integer 8 bit and then rgb8 to be able to save the RGB image in jpg format

s2.change_dtype("uint8")
s2.change_dtype("rgb8")
s2.save("rgb16_image_saved_as_jpg.jpg", overwrite=True)

Total running time of the script: (0 minutes 1.276 seconds)

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