This document discusses image processing techniques including histograms, filters, and the median filter. It defines a histogram as a graphical representation of pixel intensity distribution in an image. Histograms display data distribution and frequency through bins representing intensity value ranges. The importance of histograms is that they provide a visual representation of data and can display large amounts of information. Filters are used in image processing to remove unwanted information or amplify features of interest. The median filter specifically removes noise by replacing pixel values with the median of neighboring pixels, making it effective for "salt and pepper" noise removal. It works by finding the median value in a pixel neighborhood matrix and using that value to smooth the image.

1. Image Processing
By. Mohamed Essam

2. What Histogram is?
An image histogram is a graphical
representation of the number of pixels in an
image as a function of their intensity.
Histograms are made up of bins, each bin
representing a certain intensity value range.

8. Importance Histogram is?
Creating a histogram provides a visual representation of
data distribution. Histograms can display a large amount
of data and the frequency. The function will calculate and
return a frequency distribution. We can use it to get the
frequency of values in a dataset.

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11. Image Colors
we’ve seen how to use color to help isolate a desired portion of
an image and even help classify an image!

12. Image Intensity
 You can identify the edges of an object by looking at an abrupt change
in intensity, which happens when an image changes from a very dark to
light area, or vice versa.
 To detect these changes, you’ll be using and creating specific image
filters that look at groups of pixels and detect big changes in intensity
 in an image. These filters produce an output that shows these edges.

13. Filters
 In image Processing filter are used to filter
out unwanted information,
 Or Amplify features of interest….

15. Median Filter
 The median filter is one of the most basic image-smoothing
filters. It’s a nonlinear filter that removes black-and-white
noise present in an image by finding the median using
neighboring pixels.

16. Median Filter
It is very effective at removing impulse noise, the “salt and
pepper” noise, in the image. The principle of the median
filter is to replace the gray level of each pixel by the
median of the gray levels in a neighborhood of the pixels,
instead of using the average operation.

18. Median Filter
 To smooth an image using the median filter, we look at the
first 3 × 3 matrix, find the median of that matrix, then
remove the central value by that median. Next, we move
one step to the right and repeat this process until all the
pixels have been covered. The final image is a smoothed
image

19. Convolution kernels
A Matrix of numbers that modifies an image.

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THANKS!
Do you have any questions?
Mhmd96.essam@gmail.com
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