Question

Homework #8 Applied Programming, ENGR 10573 Spring 2018 Due Monday, Apr. 2 uploaded through TCU Online by 11:59 PM. Upload one script or function, named studentlastn ame-homework 8 ) n a single m- file that runs each problem. The homework problems should run sequentially showing I figure and or plots along with the proof that each problem works correctly. The single m-file that you turn in is the code that will be graded. Open a new figure for every problem (not every image/plot) by using the figure command. Use of subplot (m, n, k) will help. g ae s 1. Open the standard image, 'cameraman.tif with the imread(. Filter and display the image with a vertical Sobel edge filter using the command, v imfilter (I,hl). Filter and display the image with a horizontat Sobel edge filter with the command, H -infilter(, h2). Display both images atong with the addition of the two Tnages.V+ 2. Open the standard image, 'cameraman.tif' with the imread function. Filter the image with an embossing filter and display the image with the same 256-element gray colormap 3. Again, open the standard image, 'cameraman.tif' with the imread() function. Filter the image with a sharpening 0 10: 1 5 -1: 0 1 0] filter and an edge filer t0 -1 0 1 4 1; 0 1 01. Display the images with the same 256-element gray colormap and comment on the differences. 4. Using the images from Problem #3, plot the histogram using the [n, v] hist (x,nbins) command for the same value of nbins. Plot the histograms in different colors on the same graph and display the results. 5. Again, open the standard image, 'cameraman.tif' and display the image. Use the imnoise () command to add 'salt & pepper' noise (sometimes called shot noise) to the image and display the result. Try and remove the added noise with a 3x3 averaging filter using AVG imfilter (I,h) and a 3x3 median filter, MED medfilt2() and display both results. State which one works better on ot the absolute convergence test. This is requiréd when the nay contain negative terms but we cannot (or do not want to) rnating series test.

Please solve problem 4 and 5 using matlab and include the screenshot of the result , thank you

Answer 1

Please find the required MATLAB code along with necessary details in comments:

clear all
close all
clc

img=imread('cameraman.tif'); % load the original image

%% Question 4
nbins = 50;
% since the resulting image from question 3 is not available, so I just
% used a filterd image (obtained using given sharpening filter) for histogram
% plotting. You can replace the this filterd image with the image obatined in
% question 3 to obatin the correct histogram plot.

filter_val=[0 -1 0; 1 5 -1; 0 -1 0]; % sharpening filter
filtered_img=imfilter(img,filter_val); % filtered image

[n,x] = hist(double(img),nbins); % histogram for original image
bar(x,n,'r'); % use bar for same colour histogram for the image

hold on
[n,x] = hist(double(filtered_img),nbins); % histogram for filtered image
bar(x,n,'b'); % use bar for same colour histogram for the image

% hold on
% edge_sharp_img=imfilter(img,filter_val); % edge filtered image
% [n,x] = hist(double(edge_sharp_img),nbins); % histogram for edge sharpened image
% bar(x,n,'g'); % use bar for same colour histogram for the image

%% QUESTION 5

noisy_img = imnoise(img,'salt & pepper'); % add salt pepper noise to image

h = ones(3,3)/9; % define 3*3 averaging filter
avg_img = imfilter(noisy_img,h); % filter the image
median_img=medfilt2(noisy_img); % obtain median filter image

% display all the images
figure;
subplot(2,2,1)
imshow(img); % display original image
title('Original Image');

subplot(2,2,2)
imshow(noisy_img); % display noisy image
title('Image with salt and pepper noise');

subplot(2,2,3)
imshow(avg_img); % display averging filter image
title('Image with average filter');

subplot(2,2,4)
imshow(median_img); % display median filtered image
title('Image with median filter');

--------------------------------- SCREENSHOT OF CODE

main-Script·m × 1 + clear all close all clc img=imread ( . cameraman. tif ' ) ; % load the original image Question 4 nbīns = 50; % since the resulting image from question 3 is not available, so I just 10 used a filterd image (obtained using given sharpening filter) for histogram % plotting. You can replace the this filterd image with the image obained % question 3 to obatin the correct histogram plot 12 13 14 15 16 17 filter val= [0-1 0; 1 5-1; 0-1 0]; filtered ing-imfilter (img , filter val); % sharpening filter filtered image [n, x] = hist (double (ing) ,nbīns) ; bar (x,n, b' % histogram for original image use bar for 3ame colour histogram for the image 19 20- 21 hold on [n, x] = hist (double (filtered img),nbīns); % histogram for filtered image bar (x,n,g % use bar for same colour histogram for the image 23 24 25 26 27 28 % hold on % edge sharp img-imfilter (img, filter val); % edge filtered image % [n, x] = hist (double (edgesharping), nbins); % histogram for edge sharpened image - - bar (x, n,' g' ) ; % use bar for same colour histogram for the image

29 30 QUESTION 5 noisy img = innoise (img,' salt & pepper'); 롬 add salt pepper noise to image 32 33- h = ones (3,3)/9; avg img = infilter (noisy img , h); median imq=medfilt2 (noisy 1mg) % define 3*3 averaging filter filter the image 35 % obtain median filter image 36 display all the images figure: 38- 39subplot (2,2,1) 40 imshow (img) title ('Original Image) % display original image subplot (2,2,2) imshow (noisy img): title( Image with salt and pepper noise) 44 - % display noisy image subplot (2,2,3) imshow (avg img) title (Image with average filter'); % display averging filter image 49 50 51 52 53 54 subplot (2,2,4) imshow (median img) title (Image with median filter) % display median filtered image

------------------------------------------ SAMPLE OUTPUT

300 250 200 150 100 50 50 100 150 200 250 300

Original Image Image with salt and pepper noise Image with average filter Image with median filter