This document discusses image processing techniques in MATLAB. It begins with an introduction to MATLAB and covers image formats, processing techniques like enhancement, restoration, watermarking, and fusion. It then provides examples of algorithms and programs for reading images, converting between color spaces and formats, filtering noise, and segmenting images. Functions covered include imread, imshow, rgb2gray, and filters like median filtering for noise removal.

1. IMAGE PROCESSING ON
MATLAB

2. ABSTRACT
1. MATLAB introduction-commands-
operators- functions-GUI
2. Image Processing Basics formats of
image, colors
3. Techniques:enhancement,restoratio
n,water
marking,cryptography,steganograph
y,image fusions
4. Algorithms-example programs

3. Introduction
 MATLAB  MATrix LABoratory
 Developed by CleveMoler in 1984 as a teaching tool
 High performance language for technical computing
 Typical uses are,
numerical computation
 Data analysis ,plotting and visualization
 Graphical user interface building
Algorithm development and modelling

4. General Purpose Commands
 clc , clear ,close all
 save
 who , whos
 cd , ls
 disp
 Version
 Pwd
 Floor,round,abs
 date

5. DIV,
 ARITHMETIC OPERATORS
 +:ADD,-:SUB,*:MATRIX MUL,/:MATRIX
 .*:ARRAY MUL,./:ARRAY DIV
 LOGICAL OPERATORS
 AND &,OR |,NOT~
 RELATIONAL OPERATORS
 <,==,>,<=,>=,~=.
 BITWISE OPERATORS
 Bitand ,bitcmp,bitor,bitmax,bitxor,
bitset,Bitget,bitshift

6. FUNCTION
S
 PLOT
 STEM
 GRID
 XLABEL
 YLABEL
 TITLE
linear plot
discrete plot
add grid lines
add X-axis label
add Y-axis label
add graph title
 SUBPLOTdivide figure window
 FIGURE
 PAUSE
create new figure window
wait for user response

7. GUI FILE&M-FILE IN MATLAB
 Usually matlab has two file formats they are,
 M-file
 Gui –file
 GUI FILE:A graphical user interface (GUI) is a user
interface built with graphical objects, such as
buttons, text fields, sliders, and menus. In general,
these objects already have meanings to most
computer users.
 M-FILE: It is built with codings,here we use coding
to run the programs.

8. USER INTERFACE CONTROLS
 Push Buttons
 Toggle Buttons
 Radio Buttons
 Checkboxes
 Popup Menus
 Edit Text
 Axes
 Static Text
 Figures

9. IMAGE PROCESSING
o Image –It is define as the group of pixels
o Image formats
o .JPG/.JPEG - Joint Photographic Experts Group
o .GIF - Graphics Interchangeable Format
o .TIFF - Tagged Image File Format
o .PNG - Portable Network Graphics
o .BMP - Bitmap format
o Applications of image processing
o Research
o Survillence
o Medical

10. oPRIMARY COLOURS
oSECONDARY COLOUR
oCODE CONVERSION

11. IMAGE PROCESSING TECHNIQUES
oEnhancement
o Restoration
oWatermarking
oCryptography
oSteganography
oFusion
o Retrieval
oSegmentation

13. WATER MARKING
• Water Marking – Embed the secret image in an
image or any type of multimedia data.
• We should hide the image without changing
original image quality.
• Water marking is used only for copyright
protection
• The applications of water marking are,
• Tele – broadcasting
• Web-applications
• There are two types of water marking they are,
• Visible water marking
• Invisible water marking

14. STEGANOGRAPHY
o Hiding a Secret data in Digital Images without affecting the
quality of Medium. This image is called as StegoImage.
Original Image
Application
Stego Image
o Send secret communication like Military applications

15. Fusion – Process of Combining two different
scanned images to get a single image having
more relevant information of those twos
Types:
Pixel Level Fusion
Feature Level Fusion
Decision Level Fusion
IMAGE FUSION
Rule1: Averaging
Rule2: Maximum
Rule3: Minimum

16. SEGMENTATION OUTPUT
Cluster1 Cluster2
Cluster3 Cluster4

17. TO READ AN IMAGE
a =imread('cameraman.tif');
imshow(a);
ADD TWO IMAGES
I = imread(‘rice.tif');
J = imread('cameraman.tif');
K = imadd(I,J,'uint16');
imshow(K,[])

18. CONVERT IMAGE TO GRAY AND
BINARY
clc;
clear;
close all
a= imread(‘peppers.png');
subplot(2,2,1);
imshow(a);
subplot(2,2,2);
b=imresize(a,[256 256]);
imshow(b);
subplot(2,2,3);
c=rgb2gray(b);
imshow(c);
subplot(2,2,4);
d=im2bw(c);
imshow(d);

19. RGB COMPONENT
a=imread(‘peppers.png’)
subplot(2,2,1);
imshow(a);
[r c p]=size(a)
R=a;
G=a;
B=a;
R(:,:,2:3)=0;
subplot(2,2,2);
imshow(R);
G(:,:,1)=0;
G(:,:,3)=0;
subplot(2,2,3);
imshow(G);
B(:,:,1)=0;
B(:,:,2)=0;
subplot(2,2,4);
imshow(B);

20. a=imread(‘rice.png’);
figure; imshow(a);
b=imnoise(a,’salt & pepper’,0.02)
Figure;
Imshow(B);
c=medfilt2(b);
Figure;
Imshow(c)
FILTER TO REMOVE THE NOISES