Homomorphic Filtering in Digital Image Processing and its Implementation in MATLAB||#DIP

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Video lecture series on Digital Image Processing, Lecture: 22,
Homomorphic Filtering in Digital Image Processing and its Implementation in MATLAB
What is Homomorphic filter?
Which are different steps in Homomorphic filtering?
Classification of frequency domain filtering
Which approach is used for Homomorphic filtering?
Where homomorphic filtering is used?
How to derive equation for Homomorphic filter?
What are the advantages of Homomorphic filtering?
MATLAB code used in the video is present at the end in Description
Digital Image Processing (DIP) using/in MATLAB

Link to download ppts/lecture notes:

#DIP
#DIPwithMATLAB
#DigitalImageProcessingUsingMATLAB
#DigitalImageProcessing
#StudywithDrDafda

Links of other lectures in the series:
1. What is Digital Image Processing?

2. Human Visual System and Elements of Digital Image Processing

3. Fundamental steps in Digital Image Processing

4. Image Sensing and Acquisition

5. Relationship between Pixels in Digital Image Processing: Neighborhood, Adjacency & Distance measures

6. Image Sampling and Quantization

7. Spatial and Intensity resolution in Digital Image Processing and its Implementation in MATLAB

8. Basics of intensity transformations and spatial filtering and implementation in MATLAB

9. Image negatives, Log and Power-Law transformations for DIP and implementation in MATLAB

10. Piecewise linear transformation function: Contrast Stretching in DIP & implementation in MATLAB

11. Piecewise linear transformation function: Intensity-level slicing in DIP and implementation in MATLAB

12. Piecewise linear transformation function: Bit-plane slicing in DIP and implementation in MATLAB

13. Histogram Equalization in DIP and its implementation in MATLAB

14. Histogram Matching/Specification in Digital Image Processing with example and perform in MATLAB

15. Fundamentals of Spatial filtering and Smoothing spatial filters in Digital Image Processing & MATLAB

16. Order statistics/Non-linear (Median, Minimum and Maximum) spatial filters in DIP with example & Implementation in MATLAB

17. Image Sharpening in Digital Image Processing||Sharpening Spatial filters with examples||HPF||MATLAB

18. Introduction to Image Enhancement in the frequency domain and different steps for filtering in the frequency domain for DIP

19. Image Smoothing in frequency domain filtering and its Implementation in MATLAB

20. Image Sharpening (HPF) in frequency domain filtering and its Implementation in MATLAB

21. Laplacian, Unsharp masking/High Boost filtering in the frequency domain filtering and its Implementation in MATLAB

% MATLAB program for Homomorphic filtering
clc;
clear all;
close all;
% Read the image
a = rgb2gray(a);
subplot(2,3,1);
imshow(a);
title('Input Image');
a = double(a);
b = a;
%constants required for the filter
D0 = 50;
GL = 0.9;
GH = 1.9;
[m,n] = size(a); % size of input image

b = b+1;% add 1 to pixels to remove 0 values which
%would result in undefined log values

log_b = log(b); % Taking log
subplot(2,3,2);
imshow(log_b);
title('Natural Logarithm');
c = fft2(log_b); % Taking the fft
subplot(2,3,3);
imshow(uint8(c));
title('Fourier transform');
dd = fftshift(c);
for u=1:m
for v=1:n
H(u,v) = (GH - GL)*(1-exp(-1*(sqrt((u-m/2)^2+(v-n/2)^2))^2/D0)^2)+GL;
end
end
subplot(2,3,4);
mesh(H);
title('Homomorphic filter');

x = dd.*H;

real_x = abs(ifft2(x));
subplot(2,3,5);
imshow(real_x);
title('Inverse fourier transform');

Final = exp(real_x);
subplot(2,3,6);
imshow(uint8(Final));
title('Filtered Image');