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Image Enhancement - Computer Graphics and Image Processing - Lecture Slides, Slides of Computer Graphics

Aligarh Muslim UniversityComputer Graphics

Main points of this lecture are: Image Enhancement, Kinds of Image Enhancement, Histogram Processing, Point Processing, Neighbourhood Operations, Spatial Domain, Enhancement Techniques, Frequency Domains, Contrast Stretching, Equalisation Transformation

Typology: Slides

2012/2013

Uploaded on 04/23/2013

ashavari
ashavari 🇮🇳

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Contents
Over the next few lectures we will look at image
enhancement techniques working in the spatial
domain:
–What is image enhancement?
–Different kinds of image enhancement
–Histogram processing
–Point processing
–Neighbourhood operations
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Download Image Enhancement - Computer Graphics and Image Processing - Lecture Slides and more Slides Computer Graphics in PDF only on Docsity!

Contents

Over the next few lectures we will look at image

enhancement techniques working in the spatial

domain:

  • What is image enhancement?
  • Different kinds of image enhancement
  • Histogram processing
  • Point processing
  • Neighbourhood operations

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A Note About Grey Levels

So far when we have spoken about image grey level

values we have said they are in the range [0, 255]

  • Where 0 is black and 255 is white

There is no reason why we have to use this range

  • The range [0,255] stems from display technologes

For many of the image processing operations in this

lecture grey levels are assumed to be given in the

range [0.0, 1.0]

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Spatial & Frequency Domains

There are two broad categories of image

enhancement techniques

  • Spatial domain techniques
    • Direct manipulation of image pixels
  • Frequency domain techniques
    • Manipulation of Fourier transform or wavelet transform of an image

For the moment we will concentrate on

techniques that operate in the spatial domain

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Image Histograms

The histogram of an image shows us the

distribution of grey levels in the image

Massively useful in image processing, especially in

segmentation

Grey Levels

Frequencies

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Contrast Stretching

We can fix images that have poor contrast by

applying a pretty simple contrast specification

The interesting part is how do we decide on this

transformation function?

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Histogram Equalisation

Spreading out the frequencies in an image (or

equalising the image) is a simple way to improve

dark or washed out images

The formula for histogram

equalisation is given where

  • r (^) k : input intensity
  • s (^) k : processed intensity
  • k : the intensity range (e.g 0.0 – 1.0)
  • n (^) j : the frequency of intensity j
  • n : the sum of all frequencies

s k = T ( rk )

=

k

j

pr rj

1

=

k

j

j

n

n

1 Docsity.com

Equalisation Examples

Images taken from Gonzalez & Woods, Digital Image Processing (2002)

^2

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Equalisation Transformation Functions

The functions used to equalise the images in the

previous example

Images taken from Gonzalez & Woods, Digital Image Processing (2002) Docsity.com

Summary

We have looked at:

  • Different kinds of image enhancement
  • Histograms
  • Histogram equalisation

Next time we will start to look at point

processing and some neighbourhood operations

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