Question #$3$: $($Image Filtering$)$

Spatial filtering is often used to modify images. We can regard the image as an input signal and the spatial filter is our system. The output of this system is obtained by doing convolution between the input image $g[x,y]$ and the filter impulse response $w[u,v].$ The output pixel $f[x,y]$ with $33$ filter can be obtained by the $2-$dimensional convolution

$f[x,y]={\displaystyle \underset{x=-1}{\overset{1}{}}}{\displaystyle \underset{v=-1}{\overset{1}{}}}w[u,v]g[x-u,y-v].$

For this question, add all code into skeleton ee$13135\_1$ab$04\_$skeleton $.$ m from Canvas. Include all code $($and functions$)$ in this one file so that everything is published to a single PIDF.

$($a$)$ Consider the filter impulse response $($also known as a kernel$)$ below. Apply this filter to the image img in the skeleton code. Use imagesc and subplot to plot the image before and after applying the filter. Use Question #$1$ as a guide. In this part and the following parts, use clim $(($:$\left[\begin{array}{cc}0& 256\end{array}\right]\}$ to make all the images show the same range of colors.

$\backslash$table$[[w[-1,-1],w[-1,0],w[-1,1]$

$*$ NEED HELP WRITING THE CODE$*$