Digital image processing l.jpg
This presentation is the property of its rightful owner.
Sponsored Links
1 / 33

Digital Image Processing PowerPoint PPT Presentation


  • 211 Views
  • Uploaded on
  • Presentation posted in: General

Digital Image Processing. Image Enhancement (Histogram Processing). Come To The LABS!. Day: Wednesday Time: 9:00 – 11:00 Room: Aungier St. 1-005 We will start by getting to grips with the basics of Scilab Lab details available at WebCT

Download Presentation

Digital Image Processing

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


Digital image processing l.jpg

Digital Image Processing

Image Enhancement

(Histogram Processing)


Come to the labs l.jpg

Come To The LABS!

Day: Wednesday

Time: 9:00 – 11:00

Room: Aungier St. 1-005

We will start by getting to grips with the basics of Scilab

  • Lab details available at WebCT

    Shortly, there will be a Scilab assignment which will count towards your final mark


Contents l.jpg

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


A note about grey levels l.jpg

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]


What is image enhancement l.jpg

What Is Image Enhancement?

Image enhancement is the process of making images more useful

The reasons for doing this include:

  • Highlighting interesting detail in images

  • Removing noise from images

  • Making images more visually appealing


Image enhancement examples l.jpg

Image Enhancement Examples

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


Image enhancement examples cont l.jpg

Image Enhancement Examples (cont…)

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


Image enhancement examples cont8 l.jpg

Image Enhancement Examples (cont…)

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


Image enhancement examples cont9 l.jpg

Image Enhancement Examples (cont…)

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


Spatial frequency domains l.jpg

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


Image histograms l.jpg

Image Histograms

Frequencies

Grey Levels

The histogram of an image shows us the distribution of grey levels in the image

Massively useful in image processing, especially in segmentation


Histogram examples l.jpg

Histogram Examples

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


Histogram examples cont l.jpg

Histogram Examples (cont…)

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


Histogram examples cont14 l.jpg

Histogram Examples (cont…)

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


Histogram examples cont15 l.jpg

Histogram Examples (cont…)

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


Histogram examples cont16 l.jpg

Histogram Examples (cont…)

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


Histogram examples cont17 l.jpg

Histogram Examples (cont…)

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


Histogram examples cont18 l.jpg

Histogram Examples (cont…)

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


Histogram examples cont19 l.jpg

Histogram Examples (cont…)

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


Histogram examples cont20 l.jpg

Histogram Examples (cont…)

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


Histogram examples cont21 l.jpg

Histogram Examples (cont…)

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


Histogram examples cont22 l.jpg

Histogram Examples (cont…)

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

A selection of images and their histograms

Notice the relationships between the images and their histograms

Note that the high contrast image has the most evenly spaced histogram


Contrast stretching l.jpg

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?


Histogram equalisation l.jpg

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

  • rk:input intensity

  • sk:processed intensity

  • k: the intensity range (e.g 0.0 – 1.0)

  • nj:the frequency of intensity j

  • n:the sum of all frequencies


Equalisation transformation function l.jpg

Equalisation Transformation Function

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


Equalisation examples l.jpg

Equalisation Examples

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

1


Equalisation transformation functions l.jpg

Equalisation Transformation Functions

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

The functions used to equalise the images in the previous example


Equalisation examples28 l.jpg

Equalisation Examples

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

2


Equalisation transformation functions29 l.jpg

Equalisation Transformation Functions

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

The functions used to equalise the images in the previous example


Equalisation examples cont l.jpg

Equalisation Examples (cont…)

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

3

4


Equalisation examples cont31 l.jpg

Equalisation Examples (cont…)

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

3

4


Equalisation transformation functions32 l.jpg

Equalisation Transformation Functions

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

The functions used to equalise the images in the previous examples


Summary l.jpg

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


  • Login