For discs in matlab with matlab file format, the first is of desired quality, the rest have to be restored. This is the code and it does not work.

matlab

$\%$ Load the images

load$(\text{'}$Discs$.$mat'$)$;

$\%$ Define filtering parameters

median$\_$filter$\_$size $=3$; $\%$ Adjust this parameter as needed

gaussian$\_$filter$\_$sigma $=1$; $\%$ Adjust this parameter as needed

bilateral$\_$filter$\_$sigma$\_$spatial $=2$; $\%$ Adjust this parameter as needed

bilateral$\_$filter$\_$sigma$\_$intensity $=20$; $\%$ Adjust this parameter as needed

$\%$ Restore each noisy image using different filters

restored$\_$image$\_$discs$2=$ medianFilter$($Discs$2,$ median$\_$filter$\_$size$)$;

restored$\_$image$\_$discs$3=$ imgaussfilt$($Discs$3,$ gaussian$\_$filter$\_$sigma$)$;

restored$\_$image$\_$discs$4=$ bilateralFilter$($Discs$4,$ bilateral$\_$filter$\_$sigma$\_$spatial,

bilateral$\_$filter$\_$sigma$\_$intensity$)$;

$\%$ Display the original and restored images

figure;

subplot$(2,2,1)$;

imshow$($Discs$1)$;

title$(\text{'}$Original Image'$)$;

subplot$(2,2,2)$;

imshow$($restored$\_$image$\_$discs$2)$;

title$(\text{'}$Restored Image $-$ Discs$2\text{'})$;

subplot$(2,2,3)$;

imshow$($restored$\_$image$\_$discs$3)$;

title$(\text{'}$Restored Image $-$ Discs$3\text{'})$;

subplot$(2,2,4)$;

imshow$($restored$\_$image$\_$discs$4)$;

title$(\text{'}$Restored Image $-$ Discs$4\text{'})$;

$\%$ Function for median filtering

function filtered$\_$image $=$ medianFilter$($image$,$ filter$\_$size$)$

filtered$\_$image $=$ medfilt$2($image$,[$filter$\_$size, filter$\_$size$])$;

end

$\%$ Function for bilateral filtering

function filtered$\_$image $=$ bilateralFilter$($image$,$ sigma$\_$spatial, sigma$\_$intensity$)$

filtered$\_$image $=$ imbilatfilt$($image$,$ 'DegreeOfSmoothing', sigma$\_$spatial,

'IntensityThreshold', sigma$\_$intensity$)$;

end

I tried this as well,

$\%$ Load images $($assuming JPG format$)$

Discs$1=$ imread$(\text{'}$Discs$1.$mat'$)$;

Discs$2=$ imread$(\text{'}$Discs$2.$mat'$)$;

Discs$3=$ imread$(\text{'}$Discs$3.$mat'$)$;

Discs$4=$ imread$(\text{'}$Discs$4.$mat'$)$;

$\%$

$\%$ Define window sizes $($experiment with different values for each

filter$)$

mean$\_$window$\_$size $=3$;

median$\_$window$\_$size $=5$;

$\%$ Mean filtering

mean$\_$filter $=$ fspecial$(\text{'}$average$\text{'},[$mean$\_$window$\_$size

mean$\_$window$\_$size$])$;

Discs$2\_$mean $=$ imfilter$($Discs$2,$ mean$\_$filter$)$;

Discs$3\_$mean $=$ imfilter$($Discs$3,$ mean$\_$filter$)$;

Discs$4\_$mean $=$ imfilter$($Discs$4,$ mean$\_$filter$)$;

$\%$ Median filtering

median$\_$filter $=$ fspecial$(\text{'}$median$\text{'},[$median$\_$window$\_$size

median$\_$window$\_$size$])$;

Discs$2\_$median $=$ imfilter$($Discs$2,$ median$\_$filter$)$;

Discs$3\_$median $=$ imfilter$($Discs$3,$ median$\_$filter$)$;

Discs$4\_$median $=$ imfilter$($Discs$4,$ median$\_$filter$)$;

$\%$ Display results $($adjust figure size as needed$)$

figure$(\text{'}$WindowTitle$\text{'},$ 'Original Image'$)$;

imshow$($Discs$1)$;

figure$(\text{'}$WindowTitle$\text{'},$ 'Discs$2-$ Noisy'$)$;

imshow$($Discs$2)$;

figure$(\text{'}$WindowTitle$\text{'},$ 'Discs$2-$ Mean Filtered'$)$;

imshow$($Discs$2\_$mean$)$;

figure$(\text{'}$WindowTitle$\text{'},$ 'Discs$2-$ Median Filtered'$)$;

imshow$($Discs$2\_$median$)$;

$\%$ Repeat for Discs$3$ and Discs$4($consider using a loop for efficiency$)$

$\%...($similar code for Discs$3$ and Discs$4)$

$\%$ Additional analysis $($optional$)$

$\%-$ Calculate metrics like Peak Signal$-$to$-$Noise Ratio $($PSNR$)$

$\%-$ Use visualization techniques to compare noise levels