This document discusses image noise reduction systems. It defines two main types of images - vector images defined by control points and digital images defined as 2D arrays of pixels. It describes different types of digital images like binary, grayscale, and color images. It then discusses image noise sources, types of noise like salt and pepper, Gaussian, speckle and periodic noise. Various noise filtering techniques are presented like minimum, maximum, mean, median and rank order filtering to remove salt and pepper noise.

1. IMAGE NOISE REDUCTION SYSTEM

2. IMAGES
• There are two types of images
• Vector Images
• Digital Images

3. VECTOR IMAGES
• Vector images made up of vectors which lead
through locations called control points.
• Each of these control points has define on the X and
Y axes of the work plain.

4. DIGITAL IMAGES
• A digital image is an 2 dim-array of real numbers.
• 2-D image is divided into N-rows and M-columns.
• The intersection of these rows & columns is known
as pixels
Origin
x
f(x,y)
y

5. TYPES OF DIGITAL IMAGES
• Binary Images (Black and White Images)
• Gray scale Images
• Color Images

6. BINARY IMAGES
• Each pixel is just Black or White.
• There is only two possible values for each pixel i.e. 0
or 1.

7. GRAY SCALE IMAGE
• Each pixel value of gray scale images normally from
0 (Black) to 255 (White)

8. COLOR IMAGES
• In color images each pixel has particular color; that
color being described by the amount of red, blue
and green in it.
• Each of these components has a range 0-255.

9. HISTOGRAM
• Histogram of image describe the intensity value of
pixels that occur in an image.

10. IMAGE NOISE
• Noise, in image, is any degradation in an image
signal, caused by external disturbance while an
image is being sent from one place to another
place via Satellite, Wireless, and Network cable.

11. SOURCE OF IMAGE NOISE
• Error occurs in image signal while an image is being
sent electronically from one place to another.
• Sensor heat while clicking an image.
• ISO factor: ISO number indicates how quickly a
camera’s sensor absorbs light, higher ISO used,
mare chance of noticeable noise.
• Size of the sensor.

12. TYPES OF IMAGE NOISE
• Salt and Pepper Noise
• Gaussian Noise
• Speckle Noise
• Periodic Noise

13. SALT AND PEPPER NOISE
• Its 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. GAUSSIAN NOISE
• Gaussian Noise is caused by random fluctuations in
the signal. its modeled by random values added to
an image.

15. SPECKLE NOISE
• Speckle noise can be modeled by random values
multiplied by pixel values of an image.

16. PERIODIC NOISE
• Periodic noise is appearance when signal is subject
to a periodic, rather than a random disturbance.

17. NEIGHBORS OF PIXEL
• In a 3X3 region a pixel p at coordinate (i,j) has 2
horizontal and vertical neighbor whose coordinates
are given in the figure:

18. SALT AND PEPPER NOISE REMOVAL
• Minimum Filtering
• Maximum Filtering
• Mean Filtering
• Rank Order Filtering
• Median Filtering
• New Generated Filtering

19. MINIMUM FILTERING
• Current pixel replace by minimum pixel value of its
neighboring pixels.

20. MAXIMUM FILTERING
• Current pixel replace by maximum pixel value of its
neighboring pixels.

21. MEAN FILTERING
• Current pixel replace by arithmetic mean of its
neighboring pixels values.

22. RANK ORDER FILTERING
• Current pixel replace by user define order of its
neighboring pixels.

23. MEDIAN FILTERING
• Current pixel replace by mid element of its
neighboring pixels.

24. NEW GENERATED FILTERING
Current pixel replace by arithmetic mean
mid-1,mid,m+1of its neighboring pixels.

25. THANK YOU