Homomorphic filtering Project

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Homomorphic filtering Project
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ECE 5256
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:
− c  D2 ( u ,v )/ D02  

H (u, v) = ( H −  L ) 1 − e 
+

 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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