Create a simulated image comprised of 5 concentric squares of: - increasing or decreasing intensity; each square is 40 intensity values lower or higher than the previous ones, - increasing height; first square is say 40x40 pixels, the second is 80x80 pixels, the third is 120x120 pixels, etc. (1) Write your own Matlab code to apply the following edge detection method: Apply Sobel operators to calculate gradient magnitude at each pixel. Show the two output images after processing the image with Sobel filters responsive to horizontal and vertical edges. Show the gradient magnitude in your report. Apply thresholding to the gradient magnitude to get the edge map. Determine the appropriate threshold. Show the edge map in your report. (2) Use Canny method to get the edge map. In this part, you can use MATLAB's "edge" function. Show the edge map in your report. (3) Add Gaussian noise with mean 0 and standard deviation 3 to this image. Use MATLAB's "randn" function. Show the noisy image in your report. (4) Repeat Section (1) and (2) and note its accuracy (what percentage of pixels are correct)? (5) Smooth your noisy image with a 3x3 mask of Gaussian smoothing filter. Examine the effect of smoothing by repeating (1) and (2), and discuss the results