Below is the image needed for this program (matlab code)

Noise required on the image:

im1=imnoise(im,gaussian,0,0.09);

im2=imnoise(im,salt & pepper,0.25);

Im3=imnoise(im,speckle,0.20)

4- Use the image in problem 1 with same noise in 2 and the global DCT method to select the small magnitude coefficients and set them to zeros. Compress the image using the following ratios Retain 2% of the coefficients. (This requires sorting the coefficients and retaining a- the largest 296, while the rest are set to zero.) b- C- Retain 10% of the coefficients. Retain 50% of the coefficients d- Find the root mean square error between the original and reconstructed images irn each case Display the input and output images of each problem. You may resize the images to small size to economize on the number of pages. 4- Use the image in problem 1 with same noise in 2 and the global DCT method to select the small magnitude coefficients and set them to zeros. Compress the image using the following ratios Retain 2% of the coefficients. (This requires sorting the coefficients and retaining a- the largest 296, while the rest are set to zero.) b- C- Retain 10% of the coefficients. Retain 50% of the coefficients d- Find the root mean square error between the original and reconstructed images irn each case Display the input and output images of each problem. You may resize the images to small size to economize on the number of pages