HELLO PLEASE HELP!!! THANKS IN ADVANCE.

Write a Matlab code to simulate noise removal. First create a noisy lenna gray scale image, by adding normal random noise to your image (In matlab, the noise can be generated using randn. You can multiple the resulting numbers by a scaling parameter, which controls the variance of the noise). Then apply an averaging filter to the noise added image. For a chosen variance of the added noise, you need to try different window sizes (from 3 3 to 7 7) to see which one gives you the best trade-off between noise removal and blurring. Hand in your program with a final report, the original noise added images at two different noise levels and the corresponding filtered images with the best window sizes. Write down your observation.

1. Take a grayscale image, for example, "Lenna" image, and add artificially generated noise in order to create a noisy image. This can be done in Matlab. For example, let A(i,j) is the pixel value of the Lenna image at location (i,j), you then generate a random number v(i,j) that follows a normal distribution with mean zero and variance sigma. You can choose your own sigma value. You should use the random noise generator "randn" function in matlab. Thus, you will get a new pixel value B(i,j) = A(i,j) + v(i,j). Run this process for all the pixels for all i and all j, then you will produce a noisy image B. This step is now complete. 2. Given the noisy image B you just generated, you will apply averaging filters to remove the noise component in image B with the purpose of restoring the image back to A. You should construct averaging filters similar to those given in Lab 6 to remove the noise. In Lab 6, the filter size (i.e., window size) is 3 by 3, you can try 3 by 3, 5 by 5, or 7 by 7 with different weights of the matrix. 3. You should also vary the value of noise variance sigma, (i.e., different noise levels) in Step 1 to investigate the impact of the filters with different window size.