Description

The required solution steps are:

1. Avoid plagiarism.

2. Do not use artificial intelligence like ChatGPT, etc.

3. Use the MATLAB program and attach a screenshot of the codes used in the program for each part.

4. Explain the solution method for each part.

5. The project requires attaching MATLAB results, including codes and images (as specified in the project).

6. List the names of the programs used in the project on the last page.

7. An attachment is available for further clarification.

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Chap4 Homomorphic filtering

Read in the image Stadium.png.

Use homomorphic filtering to enhance the image by brightening the dark areas of the image.

The process was discussed in the slides and is in section 4.9. The process is to take the natural

logarithm of an image, then take its DFT, filter in the frequency domain, perform the inverse DFT,

then take the exp of the result. The process is described as:

The filter in the frequency domain should be radially symmetric. The filter in the text is:

H u v( , ) = (

H

− L) 1

−e−c D u v D

2( , )/ 2

0

+ L

with parameters H, L, and c, and D0. The value L should be < 1 to attenuate low spatial
frequencies, and H should be > 1 to boost the high frequencies. H(u,v) in this case is based on a

Gaussian, so c controls the slope and D0, the pass frequency.

Adjust these parameters to get the best possible looking image.

You don’t have to use this filter. If not, use some sort of high-pass filter that you can adjust with

some parameters.

To read in the image do the following:

Image1=imread(‘Stadium.png’);

K=rgb2gray(Image1);

Image1=double(K);

The image should be a grayscale image that has a maximum value of 255 and a minimum of 0.

When displaying the image use the command: colormap(gray)

Turn in:

• A description of what you did.

• the original image.

• Indicate the filter you used, and the parameters used with that filter.

• The final image.

• Your matlab code

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