Introduction

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

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