Computing linear filters in scikit-image/python.

Create a 3-by-3 matrix that has positive 8 at the center and -1 elsewhere. Open a grayscale image (any image of your choice). Filter the grayscale image with the 3-by-3 matrix.

Write your own code to implement these filters:

1)

[0,0,0] [0,1,0] [0,0,0]

2)

[0,0,0]

[0,0,1]

[0,0,0]

3) compute Im + (Im - Im*average_filter) #where * is a convolution operation and Im any image

Project 2) Take an image corrupted with salt & pepper noise. Apply a median filter to remove the noise. Also, apply a Gaussian filter to the same noisy image. Which filter was more successful? You can use any scikit-image functions you like.