MATLAB LECTURE 1
Basic Concepts of Digital Image Processing
IMAGE PROCESSING BASIC CONCEPT
IP Basic Concepts
 In this lecture we will introduce some basic
image processing concepts, including reading and
showing image, performing some image
enhancement operations on images, and getting
information about an image.
 Step 1: Read and Display an Image
 Step 2: Check How the Image Appears in the
Workspace
 Step 3: Image Sampling (Resizing Image)
 Step 4: Image Quantization (Gray Level
Reduction)
 Step 5: Converting RGB image into grayscale
intensity image.

STEP 1: READ AND DISPLAY AN
IMAGE
To Clear Matlab workspace, variables, and figure
windows.
>> close all
 To read an image, use the imread command.
 In the example below reads one of the sample
images included with IPT, pout.tif, and stores it
in an array named I.
Example : >> I = imread('pout.tif');
 To display the image, Use the imshow command
>> imshow(I)

STEP 2: CHECK HOW THE IMAGE
APPEARS
IN THE WORKSPACE
The Workspace browser displays information
about all the variables you create during a
MATLAB session. The imread function returned
the image data in the variable I, which is a 291by-240 element array of uint8 data. MATLAB can
store images as uint8, uint16, or double arrays.
 You can also get information about variables in
the workspace by calling the whos command.
>>whos
Name
Size
Bytes
Class
I
291x240
69840
uint8 array

STEP3: IMAGE SAMPLING
MATLAB: IMRESIZE









Resize an image
To change the size of an image, use the imresize
function.
Using imresize, you can specify the size of the output
image, specify the interpolation method used, and
specify the filter to use to prevent aliasing.
Resize Syntax:
B = imresize(A,m)
B = imresize(A,m,method)
B = imresize(A,[mrows ncols],method)
B = imresize(...,method,n)
B = imresize(...,method,h)
DESCRIPTION OF IMRESIZE



B = imresize(A,m) returns an image B that is m times the
size of A, using nearest-neighbor interpolation.
B = imresize(A,m,method) returns an image that is m times
the size of A using the interpolation method specified by
method.
B = imresize(A,[mrows ncols],method) returns an image of
the size specified by [mrows ncols]. When the specified
output size is smaller than the size of the input image, and
method is 'bilinear' or 'bicubic', applies lowpass aliasing.
EXAMPLE: SAMPLING (EXAMPLE OF
RESIZE)
STEP 4: IMAGE QUANTIZATION (GRAY LEVEL
REDUCTION)
The quantization used to reduce the number of
gray levels.
 Reducing the number of gray levels using the
floor function.
 Floor function is used in the following sytax:

X = floor(y/2)*2;
 It is used to reduce the gray levels in an image.
 You can divide many times according to the given
gray level to see how the image is resulting from
reducing the gray levels as in the following figure:

IMAGE QUANTIZATION EXAMPLE
CONVERTING IMAGE TYPES
STEP 5: CONVERTING RGB IMAGE
INTO GRAYSCALE INTENSITY IMAGE.
rgb2gray
 Converts RGB image to grayscale.
 Syntax
 I = rgb2gray(RGB)
 Description
 I = rgb2gray(RGB) converts the truecolor image
RGB to the grayscale intensity image I.

