Please provide a solution for Question 3 along with result to this, it is from Digital Image Processing. Again Just need Question 3.Thank you in Advance

The format for the above bonemarr image is .tif

Use Matlab to implement the following on 'blood.gif image. 1- Filter the image (you may use Imfilter) using the following operators a- Sobel b- Roberts c- Prewitt d- 5x5 sobel mask 2 812 8-2 0 12 8 2 4 2- Use Matlab to implement average and median filters using the following size templates a- 3x3 b- 5x5 c- 9x9 d- 9xl followed by 1x9 Display the input and output images. Calculate the root mean square error for each case Construct a table that ranks the RMSE(root mean square error) for each case from lowest to highest 3- Repeat problem 1 and 2 for the 'bonemarr.tif image after applying noise to it You may use the following command to add noise to the image file Im-imread('lena.tif); Iml-imnoise(im,'gaussian',0,0.25); Im2-imnoise(im,'salt & pepper',0.35); Im3-imnoise(im,'speckle',0.06); Where iml, im2, im3 are the resulted noisy images The first parameter is the original image, the second parameter is noise type the third and fourth are the mean and variance of the noise Use Matlab to implement the following on 'blood.gif image. 1- Filter the image (you may use Imfilter) using the following operators a- Sobel b- Roberts c- Prewitt d- 5x5 sobel mask 2 812 8-2 0 12 8 2 4 2- Use Matlab to implement average and median filters using the following size templates a- 3x3 b- 5x5 c- 9x9 d- 9xl followed by 1x9 Display the input and output images. Calculate the root mean square error for each case Construct a table that ranks the RMSE(root mean square error) for each case from lowest to highest 3- Repeat problem 1 and 2 for the 'bonemarr.tif image after applying noise to it You may use the following command to add noise to the image file Im-imread('lena.tif); Iml-imnoise(im,'gaussian',0,0.25); Im2-imnoise(im,'salt & pepper',0.35); Im3-imnoise(im,'speckle',0.06); Where iml, im2, im3 are the resulted noisy images The first parameter is the original image, the second parameter is noise type the third and fourth are the mean and variance of the noise