Title: Image Enhancement System. Our project was in MATLAB simulation.. All the work we have done on images... This was our presentation done on our finel viva in International confrence 2013.. thanks honorable Sir Salman AWKUM.. This man helped us much..

2. Project Members

 Muhammad Hammaad Zubair
 Roll Number 30(A)
 Nauman Ali
 Roll Number 41(A)

3. Project Title

Image Enhancement
System

4. Introduction

 Image enhancement is the improvement of digital
image quality, This improvement includes filtering
of the image and noise removal as well, In which
degraded image can be restored

5. Project Description And
Aims

 The main theme of this project is to open an image
and then apply the image processing
techniques, these techniques may include,
 Noise removal filtering
 Image enhancement

6. Image Processing

 Definition: Image processing, deals with the type of
signals for which the input is an image and the
output is also an image or parameters related to the
image. As its name suggest, it deals with the
processing on images
Image
Input
Image
Processing
Output

7. Types of image processing

 Analog images:
Analog image processing refers to the
alteration of image through electrical mean
For example: Television image
 Digital image:
Digital image processing refers processing
of the image in digital form (0,1)
For example: Digital camera

8. Applications of Image
Processing

 Medical:
X-ray, MRI, CAT etc
 Google map:
satellite/aerial views of land etc
 Industry:
inspection of items, products etc
 Law enforcement:
finger prints etc

9. Advantages of digital
image processing

 It can avoid problems such as the building up of
noise and signal distortion during processing
 Digital image processing may be modeled in the
form of multidimensional system
 Digital image processing provide real instant images.
 Processing is easy, efficient as more
 It has good accuracy, small physical cells and very
flexible

10. Noise

 Noise is unwanted undesired variations in pixel
intensity values captured or transmitted image,
 Gaussian noise
 Speckle noise
 Salt and pepper noise

11. Gaussian noise

 Definition:
variations in intensity
drawn from a Gaussian
normal distribution

12. Speckle noise

 Definition:
Speckle noise is a
granular
noise
that
inherently exists in and
degrades the quality of the
active radar and synthetic
aperture radar images

13. SALT AND PEPPER
NOISE

 Salt and pepper noise is
also known as Impulse
Noise.This noise can be
caused by sharp &
sudden disturbances in
the image signal, Its
appearance is randomly
scattered white or black
(or both) pixel over the
image.

14. Filter

 Filter is the process of removing some unwanted
signals or noise from picture
 We will apply some filter to remove background
noise from the image




Gaussian filter
Mean filter
Median filter
Set filter manually

15. Gaussian Filter

 Gaussian filters weigh pixels based on their distance
to the Location of convolution
 Blurring noise while preserving features of the image
 Smoothing the same in all directions
 More significance to neighboring pixels
 Gaussian filter removes the Gaussian noise

16. Gaussian cont..


17. Gaussian cont..


18. Gaussian cont..

 3x3 mask, Sigma 0.5

19. Gaussian cont..

 3x3 mask, Sigma 5

20. Gaussian cont..

 3x3 mask, Sigma 10

21. Average Filter

 Mean filter
 How it works

22. Average filter Cont..

 Mean filter is simple, and easy to implement method
for smoothing image
For example: reducing the amount of intensity
variation between one pixel and the next. It is open
used to reduce noise in images
 It is linear filter

23. Average filter cont..


24. Median Filter

 Median filter.
 How it works.
 Remove salt and pepper noise.

25. Median filter

 The median of the pixel value of the window is
computed, and then the center pixel of the window
is replaced with the computed median value
 The calculation of median is done is first sorting all
the pixel value neighborhood (either ascending or
descending order) and then replacing the pixel being
considered with the middle pixel value
 Median filter is non linear

26. Median Filter cont..

 Neighbors of mid value
by mask
 Arrange all in ascending
order
 Pick the mid value and
replace it with mid of
mask

27. Median filter cont..


28. Median filter cont..


29. Project slideshow

Gaussian Noise

30. Project slides cont..

Speckle Noise

31. Project slides cont..

Salt and Pepper noise

32. Project slides cont..

Gaussian filter

33. Project slides cont..

Median filter

34. Project slides cont..

Average filter

35. Project slides cont..

Set Filter Manually

36. Conclusion

 We were working on image processing for noise
reduction system which can be used for image
enhancement and removing different types of noise
occurred in image while transferring or scanning
data.
 Future work will be on videos In Sha Allah

37. 