Need Matlab code for problem below:

Read in an image and compute the Radon transform and its inverse using the commands

radon and iradon respectively, display the results, and measure the MSE. When taking

the forward transform, be sure to use enough angle resolution to give reasonable results

$($a minimum of one projection every $1$ degree$).$

When calculating the inverse transform on a computer there will be an error when

compared to the original image. Use four different combinations of filters and

interpolations in the inverse Radon command and indicate which one gives the best

result for your input image determined by the lowest mean squared error $($MSE$)$ between

the original image and the reconstructed image.

The MSE is a scalar value that is the sum of $(($original image $-$ reconstructed

image$).^2)/($number of pixels in an image$).$

FILTER is a string or a character vector that specifies any of the

following standard filters:

'Ram$-$Lak' The cropped Ram$-$Lak or ramp filter $($default$).$ The

frequency response of this filter is $|f|.$ Because this

filter is sensitive to noise in the projections, one of

the filters listed below may be preferable.

'Shepp$-$Logan' The Shepp$-$Logan filter multiplies the Ram$-$Lak filter by

a sinc function.

'Cosine' The cosine filter multiplies the Ram$-$Lak filter by a

cosine function.

'Hamming' The Hamming filter multiplies the Ram$-$Lak filter by a

Hamming window.

'Hann' The Hann filter multiplies the Ram$-$Lak filter by a

Hann window.

'none' No filtering is performed.