**What is Digital Image Processing?**

1. An image may be defined as a two dimensional function f(x,y), where x

and y are spatial coordinates.

2. Amplitude of f at any pair of coordinates (x,y) is called intensity or gray

level of the image at that point.

3. When x, y, and amplitude values of f are all finite, discrete quantities,

image is said to be a digital image.

4. Hence, digital image processing refers to processing digital images by

means of a digital computer.

5. As a digital image is composed of a finite number of elements , each of

which has a particular location and a value.

6. These elements are referred to as picture elements, image elements,

pels, and pixels.

7. Pixel is the most widely used term to denote the elements of an image.

8. Moreover, digital image processing encompasses processes whose

inputs and outputs are images and, in addition, encompasses processes

that extract attributes from images, up to and including the recognition of

individual objects.

**Background on MATLAB and the Image Processing Toolbox**

1. MATLAB stands for MATrix LABoratory.

2. It was written originally to provide easy access to matrix software

developed by LINPACK and EISPACK projects.

3. MATLAB engines incorporate the LAPACK and BLAS libraries,

constituting the state of the art in software for matrix computation.

Background on MATLAB and the Image Processing Toolbox

4. MATLAB is a high level language for technical computing.

5. Its typical uses include:

a. Math & computation

b. Algorithm development

c. Data acquisition

d. Modeling & simulation

e. Data analysis, exploration, and visualization

f. Scientific and engineering graphics

g. Application development, including GUI building.

6. MATLAB is complimented by an application specific solutions family

called toolboxes.

7. The Image Processing toolbox is a collection of MATLAB functions that

extend the capability of MATLAB environment for the solution of image

processing problems.

8. There are various other toolboxes such as Signal processing, fuzzy logic,

and wavelet toolboxes, which are sometimes used to compliment IPT.

**Areas of Image Processing covered in tutorials**

1. The areas that must be covered in this tutorial will be:

a. DIP fundamentals

b. Intensity transformations and spatial filtering

c. Processing in the frequency domain

d. Image restoration

e. Color Image Processing

f. Wavelets

g. Image compression

h. Morphological image processing

i. Representation & Description

j. Object Recognition

**MATLAB desktop**

MATLAB environment consists of following main parts

1. Command Window

2. Command History

3. Workspace

4. Current Folder

5. Editor Window

**Command Window**

1. Main window in MATLAB.

2. Used to enter variables.

3. Used to run functions and

M-file scripts.

4. All commands are typed after

command prompt “>>”.

**Command History**

1. Statements entered in

command window are logged

in Command History.

2. View and search previously

run statements.

3. Copy and execute selected

statements.

**Workspace**

1. List all variables used as long

as MATLAB has opened.

2. Type “who” in command

window to list all the

commands used.

3. Type “whos” to list all the

commands with current

values, dimensions, etc.

4. “clear” command is used to

clear all the variables from

workspace.

5. Save all the variables and data

to text file (.mat file) to use it

for later.

**Current Folder**

1. Lists all m files, etc. available

in current directory.

2. Set working folder as current

directory or as a part of the

search path so that MATLAB

will find the files easily.

**Editor**

1. Used to create scripts and

m-files.

2. Click the “New Script” button

in the Toolbar.

**“Help” System**

1. Type “help” in command

window to go through various

topics.

2. Type “help elfun” (Elementary

Math Function), and MATLAB

will list all the functions

according to specific

category.

3. “help” command is used to get specific help about this function.

4. To open the help window on the specific topic of interest, use “doc” command.

5. help keyword is used to get

help for a specific function,

but lookfor command is used

to search for all functions, etc.

with a specific keyword.

6. Example: >>lookfor plot