This document provides an introduction and overview of image processing using Matlab. It discusses the basics of Matlab including its environment, syntax, variables, vectors and matrices. It then covers image processing topics such as importing and exporting images, viewing histograms, and applying filters like box filters and linear filters to images. The document is intended to teach the fundamentals of working with images in the Matlab programming language.

1. Image processing using Matlab
Author : Pooya Sagharchi Ha

2. Agenda
• Introduction to Matlab
• Basics & Examples
• Image processing with Matlab
• Basics & Examples

3. What is Matlab?
• Matlab stand for Matrix Laboratory
• Matlab is high-level language
• perform computationally intensive tasks faster
than with traditional programming languages
such as c++
• The help in Matlab is very good, use it!
• Everything is treated as a matrix

4. The Matlab Environment
• Matlab window components:
• Workspace
• Displays all the defined variables
• Command window
• To execute commands in the Matlab
environment
• File editor window
• Define your functions

5. Matlab Help
• Matlab help is an extremely powerful assistance
to learning Matlab
• Help not only contains the theoretical
background, but also shows demos for
implementation
• Matlab help can be opened by using the HELP
pull-down menu

6. Basics syntax
• Comment : ctrl + / OR %
• Uncomment : ctrl + t
• Semicolon : suppress printing
• Arithmetic operators:
+ addition
- subtraction
* multiplication
^ power
' transpose
left division
/ right division

7. • Variable :
>> 2 * 25 + 6 * 22 + 100 / 2
ans =
232
>> a = 25; b = 22;
>> d = a * b
ans =
550
sqrt
returns the
square root of
each element of
the array X
abs
absolute value for
real numbers
cos cosine function
sin sin function
exp
exponential
function

8. • Who, Whos : current variables in the workspace
• Save : save workspace variables to *.mat file
• Load : load variables from *.mat file
• Clear : clear workspace variables
• Clc : clear command window
• Close : closes the current figure window

9. Vectors and Matrices
• How to build a matrix?
>> a = [1 5 8]
a =
1 5 8
>> a = [ 1 2 3]'
a =
1
2
3

10. >> a = [ 0:2:4 ; 8:1:10; 35:5:45]
a =
0 2 4
8 9 10
35 40 45
>> a = [1:3; 4:6; 7:9]
a =
1 2 3
4 5 6
7 8 9

11. • A particular element of a matrix can be
assigned:
>> a(3,2)
ans = 40
• Place the number 5 in the first row, second
column:
• >> a(3,2) = 29

12. • Operations ad functions that were defined scalars
in the previous section can also be used on
vectors and matrices, For example.
>> a = [ 1 2 3];
>> b = [ 4 5 6];
>> c = a + b
c =
5 7 9

13. • Special matrices:
• zeros(n,m) : n*m matrix of zeros
• ones(n,m) : n*m matrix of ones
• eye(n) : n*n identity matrix
• rand(n) : n*n random matrix

14. Flow Control
• Matlab has five flow control constructs:
1. if statement
2. for loop
3. while loop
4. break statement

15. if
• If statement condition
• The general form of the IF statement is
IF expression
statements
ELSEIF expression
statements
ELSE
statements
END

16. • Example:
s = input(‘Please enter a scalar value =‘);
if s > 1
error(‘Error!’);
else
disp(‘ok’);
end

17. for
• FOR repeats statements a specific number of
times
• The general form of a FOR statement is:
FOR variable = expression
statements
END

18. for i=1:10
x(i) = sin(i * pi / 10);
end;
for i=[ 1, 2, 3, 7]
x(i) = i + 1;
end;

19. while
• WHILE repeats statements an indefinite number
of times
• The general form of a WHILE statement is:
• WHILE expression
• statements
• END

20. t = 1;
while t ~= -1
t = input(' enter ..... ');
end

21. Scripts and Functions
• There are two kinds of M-files:
• scripts, which do not accept input arguments
or return output arguments. They operate on
data in the workspace.
• Functions, which can accept input arguments
and return output arguments. Internal
variables are local to the function.

22. function
function [ output_args ] = functionName( input_args )
%functionName Summary of this function goes here
% Detailed explanation goes here
end

23. function Z=fitness(x)
Z=sum(x.^2);
end

24. Visualization and Graphics
• Plot ( x, y) : plot 1D function
• figure : open a new figure
• hold on, hold off : refreshing
• title(‘figure title) : add title to figure

25. Image Processing

26. Matlab and images
• An image in Matlab is treated as a matrix
• Every pixel is a matrix element

27. Image import and Export
• Read and write images in Matlab:
image = imread(‘image fileName.format');
figure;
imshow(image);
imwrite(image, ‘new image filename.format');

28. Images and Matrices
row = 256;
col = 256;
img = zeros(row, col);
img(100:105, :) = 0.5;
img(:, 100:105) = 1;
figure;
imshow(img);
Column 1 to 256
Ro
w 1
to
25
6
o
[0, 0]
o
[256, 256]

29. Histograms
• Frequency of the intensity value of the image
• Quantize frequency into intervals
• Probability density function of image intensities

30. img = imread(‘image Filename.image format’);
imshow(img);
figure;
imhist(rgb2gray(img));

31. Image Filtering
• Let’s replace each pixel with a weighted average
of its neighborhood.
• The widths are called the filter kernel
• What are the weighs for the average of a 3*3
neighborhood?
111
111
111
“box filter”

32. Image Filtering
I = imread(‘filename.format file’);
h = fspecial(‘unsharp’);
I2 = imfilter(I,h);
imshow(I2);

33. Liner filter
000
010
000
Filtered
(no change)
Original

34. Liner filter
Shifted left by 1 pixel
Original
000
100
000

35. Liner filter
Bluer( with box
filter )
Original
111
111
111