Help Sally restore her graduation photo
You are going to combine all the knowledge you acquired throughout the course to complete a final challenge: reconstructing a very damaged photo.
Help Sally restore her favorite portrait which was damaged by noise, distortion, and missing information due to a breach in her laptop.
damaged_image.You will be fixing the problems of this image by:
- Rotating it to be uprightusing
rotate() - Applying noise reduction with
denoise_tv_chambolle() - Reconstructing the damaged parts with
inpaint_biharmonic()from theinpaintmodule.
show_image() is already preloaded.
This exercise is part of the course
Image Processing in Python
Exercise instructions
- Import the necessary module to apply restoration on the image.
- Rotate the image by calling the function
rotate(). - Use the chambolle algorithm to remove the noise from the image.
- With the mask provided, use the biharmonic method to restore the missing parts of the image and obtain the final image.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Import the necessary modules
from skimage.restoration import denoise_tv_chambolle, ____
from skimage import transform
# Transform the image so it's not rotated
upright_img = ____(damaged_image, 20)
# Remove noise from the image, using the chambolle method
upright_img_without_noise = ____(upright_img,weight=0.1, multichannel=True)
# Reconstruct the image missing parts
mask = get_mask(upright_img)
result = ____.____(upright_img_without_noise, mask, multichannel=True)
show_image(result)