imaging fundamentals

8/7/2019 Imaging Fundamentals

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Course Website: http://www.comp.dit.ie/bmacnamee

Digital Image Processing:Digital Imaging Fundamentals

Brian Mac [email protected]
mailto:[email protected]:[email protected]


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Contents

This lecture will cover:

Human visual system

Light and the electromagnetic spectrum

Image representation

Image sensing and acquisition

Sampling, quantisation and resolution


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Human Visual System

The best vision model we have!

Knowledge of how images form in the eyecan help us with processing digital images

We will take just a whirlwind tour of thehuman visual system


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Structure of the Human Eye

The lens focuses light from objects onto theretina

The retina is covered withlight receptors called

cones(6-7 million) androds(75-150 million)

Cones are concentrated

around the fovea and arevery sensitive to colour

Rods are more spread outand are sensitive to low levels of illumination


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Blind-Spot Experiment

Draw an image similar to that below on apiece of paper (the dot and cross are about6 inches apart)

Close your right eye and focus on the cross

with your left eyeHold the image about 20 inches away from

your face and move it slowly towards youThe dot should disappear!


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Image Formation in the Eye

Muscles within the eye can be used tochange the shape of the lens allowing usfocus on objects that are near or far away

An image is focused onto the retina causing

rods and cones to become excited whichultimately send signals to the brain


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Brightness Adaptation & Discrimination

The human visual system can perceiveapproximately 1010 different light intensitylevels

However, at any one time we can only

discriminate between a much smallernumber brightness adaptation

Similarly, the perceived intensityof a regionis related to the light intensities of theregions surrounding it


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Brightness Adaptation & Discrimination(cont)

An example of simultaneous contrast

An example of Mach bands


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Optical Illusions

Our visualsystems play lotsof interestingtricks on us


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Light and the Electromagnetic Spectrum

Light is just a particular part of theelectromagnetic spectrum that can besensed by the human eye

The electromagnetic spectrum is split up

according to the wavelengths of differentforms of energy


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Reflected Light

The colours that we perceive are determinedby the nature of the light reflected from anobject

For example, if white

light is shone onto agreen object most

wavelengths areabsorbed, while greenlight is reflected from

the object

WhiteLight

ColoursAbsorbed

GreenLight


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Sampling, Quantisation and Resolution

In the following slides we will consider whatis involved in capturing a digital image of areal-world scene

Image sensing and representation

Sampling and quantisation Resolution


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Image Representation

col

row

f (row, col)

Before we discuss image acquisition recallthat a digital image is composed of M rows

and Ncolumns of pixelseach storing a value

Pixel values are mostoften grey levels in therange 0-255(black-white)

We will see later onthat images can easilybe represented asmatrices


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Image Acquisition

Images are typically generated byilluminatinga sceneand absorbing the

energy reflected by the objects in that scene Typical notions of

illumination andscene can be way off:

X-rays of a skeleton

Ultrasound of anunborn baby

Electro-microscopic

images of molecules


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Image Sensing

Incoming energy lands on a sensor materialresponsive to that type of energy and this

generates a voltage

Collections of sensors are arranged to

capture images

Imaging Sensor

Line of Image SensorsArray of Image Sensors


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Image Sampling and Quantisation

A digital sensor can only measure a limitednumber of samples at a discrete set of

energy levels

Quantisationis the process of converting a

continuous analogue signal into a digitalrepresentation of this signal

17 Image Sampling and Quantisation


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Image Sampling and Quantisation(cont)

Remember that a digital image is alwaysonly an approximation of a real world

scene

18


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Spatial Resolution

The spatial resolutionof an image isdetermined by how sampling was carried out

Spatial resolution simply refers to thesmallest discernable detail in an image

Vision specialists willoften talk about pixelsize

Graphic designers willtalk about dots per

inch(DPI)

5.1

Megapixe

ls

19


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Spatial Resolution (cont)

1024 * 1024 512 * 512 256 * 256

128 * 128 64 * 64 32 * 32

20


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Intensity Level Resolution

Intensity level resolutionrefers to thenumber of intensity levels used to represent

the image The more intensity levels used, the finer the level of

detail discernable in an image

Intensity level resolution is usually given in terms ofthe number of bits used to store each intensity level

Number of BitsNumber of Intensity

Levels Examples

1 2 0, 1

2 4 00, 01, 10, 11

4 16 0000, 0101, 11118 256 00110011, 01010101

16 65,536 1010101010101010

21


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Intensity Level Resolution (cont)

128 grey levels (7 bpp) 64 grey levels (6 bpp) 32 grey levels (5 bpp)

16 grey levels (4 bpp) 8 grey levels (3 bpp) 4 grey levels (2 bpp) 2 grey levels (1 bpp)

256 grey levels (8 bits per pixel)

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Resolution: How Much Is Enough?

The big question with resolution is alwayshow much is enough?

This all depends on what is in the image andwhat you would like to do with it

Key questions include Does the image look aesthetically pleasing?

Can you see what you need to see within the

image?


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Summary

We have looked at:

Human visual system

Light and the electromagnetic spectrum

Image representation

Image sensing and acquisition Sampling, quantisation and resolution

Next time we start to look at techniques forimage enhancement

imaging fundamentals

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