This repo includes the homeworks I have done for EE409 course. In this course, we covered many topics that are fundamental to digital image processing and practiced them with mini project assignments using MATLAB.
I have listed the questions in the assignments below:
Q: In this part, you will plot the values of the pixels in a row you select in your double grayscale image(use subplot). From the graph, try to find in which pixel the brightness is the highest. Then indicate the row you have plotted by making that row white and display using imshow (use subplot).
Q: Take the horizontal first order derivative of your double grayscale image(without white line). Then plot the same row (which you selected in Q1) of your image derivative (use subplot). What are the meanings of positive and negative derivative values? Draw a white line on the same row of the image derivative as in question 1 and display (use subplot).
Q: Take the horizontal second order derivative of your double grayscale image(without white line) and take its absolute value. Then plot the same row of your image as in Q1 (use subplot. Draw a white line on the same row of the derivative image as in previous questions and display (use subplot).
Q: Sharpen your double grayscale image using “High-Boost” sharpening method with just applying a single mask to your image. Display the sharpened image (use subplot). Try to obtain a visually pleasant sharp image as much as you can.
Q: Sharpen your double grayscale image using “Unsharp Masking” method with 3x3 weighted averaging filter. First apply the weighted averaging filter to your image and display the result (use subplot). Then use it for “Unsharp Masking” sharpening of your image and display the sharpened image (use subplot). Try to obtain a visually pleasant sharp image as much as you can.
Q: Write a Matlab script with a double for loop to implement dilation morphological operation and dilate your binary image with the 3x3 structural element “se1=[1 1 1; 1 1 1; 1 1 1]”. (Don’t use morphological operation functions in Matlab such as imdilate();)
Q: Write a Matlab code that finds the edges of your name by using morphological operations.
Q: Use morphological operations to clear your name with smallest (10+d) font size while preserving the others. Then clear smallest(10+d) and medium(25+d) size texts while preserving the largest(35+d) text. Note that after the operations the texts on your images should be readable although there might be some distortions. Try to merge broken letters. Show the images obtained in every step (after each operation) using subplot.
Q: Write a Matlab code that automatically detects the longest horizontal word (that has largest width) in your name by using morphological operations.
Q: Delete the horizontal text while preserving the vertical. Show the images obtained in every step (after each operation) using subplot.
Q: Write the Matlab command for finding the histogram of your double grayscale image. You will obtain a figure as given right as an example. Display and report your grayscale image together with its histogram side by side in the same figure window and comment on where most of the pixels are distributed heavily.
Q: This time find the histogram of your double grayscale image using 3 bins and assign the histogram output to a variable. Normalize the histogram result by dividing it to the total number of pixels in the image. Plot the histogram of your image by using the "bar()" command and report the graph together with your grayscale image side by side in the same figure window. Write the percentages of pixels in "dark gray", "medium gray" and "light gray" bins.
Q: Now, you will apply piecewise linear transformation with 2 linear pieces to enhance the double grayscale image. Try a few different parameters and report the results. Determine and report the best parameters (a and ya) as you can to enhance your image. Remember that L=1 for double grayscale images. Display and report the obtained images and their histogram side by side in the same figure window.
Q: Try to enhance the contrast of the original double grayscale image using gamma transformation. Determine and report the best parameters as you can to enhance your image. Display and report the transformed image and its histogram side by side in the same figure window.
Q: Enhance the contrast of the original double grayscale image by using the histogram equalization method and adaptive histogram equalization method. Display and report the resultant images together with previous low contrast image side by side in the same figure window.
Q: Write your own Matlab code to add random values(noise) between -0.2d and +0.2d (if the last digit of your ID is 7, then -0.27 and +0.27) to every pixel of your images. Do not use “imnoise” function. Repeat it by adding random values between -0.3d and +0.3d. Display and report the resultant images side by side in the same figure window. Draw the histograms of the original and the noisy yourName _gray images side by side in another figure. Comment on the results briefly.
Q: Write your own Matlab code to add Gaussian random noise with μ=0 and σ=0.1d (if the last digit of your ID is 7, then σ=0.17) to every pixel of your images. Do not use “imnoise” function. Repeat it with μ=0 and σ=0.2d. Display and report the resultant images side by side in the same figure. Draw the histograms of the original and the noisy yourName _gray images side by side in another figure. Comment on the results briefly.
Q: Write your own Matlab code to add 1d% (if the last digit of your ID is 7, then 17%, i.e. the probability of a pixel to be noisy should be 0.17) salt&pepper noise to your images. Do not use “imnoise” function. Repeat it by adding 2d% salt&pepper noise. Display and report the resultant images side by side in the same figure. Draw the histograms of the original and the noisy yourName _gray images side by side in another figure. Comment on the results briefly.
Q: Write your own Matlab function(with a double for loop) to make a 3x3 pixel median filter (No padding, DO NOT USE medfilt, medfilt2, ordfilt2, imfilter, conv2 functions). Denoise your salt&pepper noised images in Part 9 with your median filter. Apply 3x3 averaging filter on the same salt&pepper noised images. Display and report the obtained images side by side in the same figure window together with their titles. Comment and compare the results. What can you do to filter more noise with median and averaging filters from the images?
Q: Generate a grayscale n x n image whose pixel values have a radial gradient from the upper left corner to the lower right corner. In other words, the value of the upper left corner pixel should be 0 (black) and the value of the pixels should increase according to their distance to the upper left corner. The pixel on the lower right corner should have 1 (white) value. (n=300+d*50, where d is the last digit of your student ID number)
Q: Write a Matlab code to generate a circular black frame around your image. (Hint: The pixels with a distance larger than a radius "r” from the center of your image must be zero)
Q: Take the logo of the university (AYBU) and change the colors of the logo according to the following color table using your last digit of your student ID number "d". Make the foreground color "d" and background color "9-d". (e.g. if d=3: Make foreground orange and background Blue)
Q: Write the Matlab commands using array indexing method that flips your color image vertically (i.e. first row becomes last row…). Display and report the resultant image.
Q: Crop a [1ab x 2ab] (where ab is the last 2 digits of your student ID number) pixels patch from the center of your color image using indexing method. Display and report the resultant patch.
Q: Write the Matlab command for drawing a vertical red line at the middle of your color image by changing the color of the corresponding pixels to just red. Write the Matlab command (using array indexing method) for drawing a yellow square box (100 pixels width&height) at the center of your color image by changing the color of the corresponding pixels to yellow. Display and report the resultant images.
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