Image enhancement introduction and discussion about morphological operators

2. Image Enhancement
• Principle objective of Image enhancement is to
process an image so that result is more suitable
than original image for specific application.
 Very first step in Digital Image Processing.
 It is purely subjective.
 It is a cosmetic procedure.
 It improves subjective qualities of images.

4. Image enhancement techniques can be divided into
different categories:
Spatial domain : - operate directly on pixels
Frequency domain : - operate on the Fourier transform of an image
Combination Methods:- There are some enhancement techniques
based on various combinations of methods from the first two
categories
Point operations: - modify the brightness value of each pixel
independently
Local operations: - modify the value of each pixel based on
neighboring brightness values

5. Enhancement Factors
• Dynamic Range of Intensity Values.
• Limited number of bit-planes.
• Varying illumination over the image space.
 Brightness
 Contrast
 Color

6. Morphological operators
• Create morphological structuring element (STREL)
• NHOOD is a matrix containing 1's and 0's; the location of the 1's defines the
neighborhood for the morphological operation.
• SE = strel('arbitrary', NHOOD) creates a flat structuring element
where NHOOD specifies the neighborhood.
NHOOD1 =[ 1 1 1;1 1 1];
NHOOD2 =[ 1 1 1;1 0 1; 0 0 0];
SE1 = strel('arbitrary', NHOOD1);
SE2 = strel('arbitrary', NHOOD2);
SE1 = Flat STREL object containing 6
neighbors.
Neighborhood:
1 1 1
1 1 1
SE2 = Flat STREL object containing 5
neighbors.
Neighborhood:
1 1 1
1 0 1
0 0 0

7. • SE = strel('arbitrary', NHOOD, HEIGHT) creates a non flat structuring
element, where NHOOD specifies the neighborhood.
• HEIGHT is a matrix the same size as NHOOD containing the height values
associated with each nonzero element of NHOOD.
• The HEIGHT matrix must be real and finite valued.
NHOOD3 =[ 1 0 0;0 0 1];
HEIGHT = [23 0 0; 0 0 5];
SE3 = strel('arbitrary', NHOOD3, HEIGHT);
SE3 = Nonflat STREL object containing 2 neighbors.
Neighborhood:
1 0 0
0 0 1
Height:
23 0 0
0 0 5

8. Morphologically open image [imopen]
SE = strel(shape, parameters)
• SE = strel('disk', R, N)
• SE = strel('rectangle', MN)
arbitrary, ball, diamond, line, octagon, pair, periodicline, square
Create morphological structuring element [strel]
• IM2 = imopen(IM,SE)
• IM2 = imopen(IM,NHOOD)

9. Morphologically open image with structuring
element disk
original = imread('snowflakes.png')
figure, imshow(original);
Create a disk-shaped structuring element with a radius of 5 pixels.
se = strel('disk',5);
Remove snowflakes having a radius less than 5 pixels by opening it
with the disk-shaped structuring element.
y = imopen(original,se);
figure, imshow(y,[]);

10. Disk Structuring Element R=3

11. original = imread('snowflakes.png')
figure, imshow(original);
Create a rectangle-shaped structuring element with 3 rows and
5 columns.
MN = [3,2];
se = strel(‘rectangle‘, MN);
Remove snowflakes having a radius less than 5 pixels by opening
It with the disk-shaped structuring element.
Opening = imopen(original,se);
figure, imshow(Opening,[]);

12. Rectangle Structuring Element N rows
and M columns

13. Thank You
Manish T I
Email: manishti2004@gmail.com
Website: www.iprg.co.in
FB: ImageProcessingResearchGroup