Digital Image Processing

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SYLLABUS
 What is Image ?
❑ An image is a spatial representation of a two-
dimensional or three-dimensional scene.
❑ An image is an array, or a matrix pixels (picture
elements) arranged in columns and rows.

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WHY…..digital image processing…???
 Interest in digital image processing methods stems from
two principal application areas:

1. Improvement of pictorial information for human

interpretation

2. Processing of image data for storage, transmission, and

representation for autonomous machine perception

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WHAT IS DIGITAL IMAGE PROCESSING?
DIP Definition:
A Discipline in Which Both the Input and Output of a
Process are Images.

Image Process Image

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What Is Digital Image ?
 An image may be defined as a two-dimensional function, f(x, y),
where x and y are spatial (plane) coordinates, and the
amplitude of f at any pair of coordinates (x,y) is called the
intensity or gray level of the image at that point.

 Digital Image:
When x, y and the intensity values of f are all finite, discrete
quantities, we call the image a digital image.

▪ Color Image:
 r ( x, y) 
f ( x, y) =  g ( x, y) 
 
 b ( x , y ) 

The field of digital image processing refers to processing digital

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images by means of a digital computer.
What Is Digital Image ?
An Image:

g(x , y)
Discretizatio
n
g(i , j)

Quantizatio
n f(i , j) Digital Image

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f(i0 , j0) : Picture Element, Image Element, Pel, Pixel
WHAT IS DIGITAL IMAGE PROCESSING?

Image
Processing Image Analysis Vision

Low-Level High-Level
Process Mid-Level Process
Process
• Reduce Noise Making Sense of an
• Segmentation Ensemble of
• Contrast Enhancement
• Classification Recognized Objects
• Image Sharpening

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Origins of Digital Image Processing
 One of the first applications of digital images was in the newspaper
industry, when pictures were first sent by submarine cable between
London and New York.

 Introduction of the Bartlane cable picture transmission system in the

early 1920s reduced the time required to transport a picture across the
Atlantic from more than a week to less than three hours.

A digital picture produced in

1921 from a coded tape by a
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telegraph printer with special
type faces.
Fields that Use Digital Image Processing
 Today, there is almost no area of technical endeavor that is
not impacted in some way by digital image processing.

 Gamma-Ray Imaging
 X-Ray Imaging
 Imaging in the Ultraviolet Band
 Imaging in the Visible and Infrared Bands
 Imaging in the Microwave Band
 Imaging in the Radio Band

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Gamma-Ray Imaging
Bone scan PET
 Major uses of imaging
based on gamma rays
include nuclear medicine.

 In nuclear medicine, the

approach is to inject a
patient with a radioactive
isotope that emits gamma
rays as it decays.

 Images are produced from

the emissions collected by
gamma ray detectors.

14 Cygnus loop Reactor valve

X-Ray Imaging
Chest
X-Ray PCB

Angiogram

15 Head CT Cygnus loop

 Applications and Research Topics

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Applications and Research Topics
 Document Handling

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Applications and Research Topics
 Signature Verification

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Applications and Research Topics
 Biometrics

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Applications and Research Topics
 Fingerprint Verification / Identification

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Applications and Research Topics
 Object Recognition

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Applications and Research Topics
 Target Recognition
Department of Defense (Army, Air force, Navy)

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Applications and Research Topics
 Interpretation of Aerial Photography
Interpretation of aerial photography is a problem domain in both
computer vision and registration.

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Applications and Research Topics
 Autonomous Vehicles
Land, Underwater, Space

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Applications and Research Topics
 Traffic Monitoring

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Applications and Research Topics
 Traffic Monitoring

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Applications and Research Topics
 Face Detection

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Applications and Research Topics
 Face Recognition

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Applications and Research Topics
 Face Detection/Recognition Research

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Applications and Research Topics
 Facial Expression Recognition

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Applications and Research Topics
 Hand Gesture Recognition
Smart Human-Computer User Interfaces
Sign Language Recognition

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Applications and Research Topics
 Human Activity Recognition

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Applications and Research Topics
 Medical Applications

skin cancer breast cancer

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Applications and Research Topics
 Morphing

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Applications and Research Topics
 Inserting Artificial Objects into a Scene

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 Fundamental Steps in Digital Image Processing

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 Fundamental Steps in Digital Image Processing

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 Fundamental Steps in Digital Image Processing
Essential steps when processing digital images:

Acquisition
Enhancement
Outputs are
Restoration
digital
Color image restoration images

Wavelets
Morphological processing
Segmentation Outputs are
attributes of the
Representation image

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Recognition
 Fundamental Steps in Digital Image Processing

 Image acquisition is the first process.

Generally, the image acquisition stage involves
preprocessing, such as scaling.

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 Fundamental Steps in Digital Image Processing
 Image enhancement is the process of manipulating an image
so that the result is more suitable than the original for a specific
application.
There is no general “theory” of image enhancement.
When an image is processed for visual interpretation, the
viewer is the ultimate judge of how well a particular method
works.

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 Fundamental Steps in Digital Image Processing

 Image Restoration is an area that also deals with improving the

appearance of an image.
However, unlike enhancement, which is subjective, image
restoration is objective, in the sense that restoration techniques
tend to be based on mathematical or probabilistic models of
image degradation.

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 Fundamental Steps in Digital Image Processing

 Color Image Processing is an area that has been

gaining in importance because of the significant
increase in the use of digital images over the Internet.

 Wavelets are the foundation for representing images

in various degrees of resolution.

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 Fundamental Steps in Digital Image Processing

 Compression, as the name implies, deals with

techniques for reducing the storage required to save
an image, or the bandwidth required to transmit it. This
is true particularly in uses of the Internet.

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 Fundamental Steps in Digital Image Processing

 Morphological processing deals with tools for

extracting image components that are useful in the
representation and description of shape.

 Segmentation procedures partition an image into its

constituent parts or objects.
A segmentation procedure brings the process a
long way toward successful solution of imaging
problems that require objects to be identified
individually.
In general, the more accurate the segmentation,
the more likely recognition is to succeed.
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 Fundamental Steps in Digital Image Processing

 Representation and description almost always follow the

output of a segmentation stage, which usually is raw pixel
data.
▪ Boundary representation is appropriate when the focus is on
external shape characteristics, such as corners and
inflections.
▪ Regional representation is appropriate when the focus is on
internal properties, such as texture or skeletal shape.
Description, also called feature selection, deals with
extracting attributes that result in some quantitative
information of interest or are basic for differentiating one
class of objects from another.

 Recognition is the process that assigns a label (e.g.,

“vehicle”) to an object based on its descriptors. Digital
image processing with the development of methods for
recognition of individual objects.
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 General Purpose Image Processing System

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 General Purpose Image Processing System

 Specialized image processing hardware usually

consists of the digitizer, plus hardware that performs
other primitive operations, such as an arithmetic logic
unit (ALU), that performs arithmetic and logical
operations in parallel on entire images.

 This type of hardware sometimes is called a front-end

subsystem, and its most distinguishing characteristic
is speed.

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 General Purpose Image Processing System

 The Computer in an image processing system is a

general-purpose computer and can range from a PC
to a supercomputer.

 In dedicated applications, sometimes custom

computers are used to achieve a required level of
performance, but our interest here is on general-
purpose image processing systems.

 In these systems, almost any well-equipped PC-type

machine is suitable for off-line image processing
tasks.
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 General Purpose Image Processing System

 Software for image processing consists of specialized

modules that perform specific tasks.

 More sophisticated software packages allow the

integration of those modules and general-purpose
software commands from at least one computer
language.

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 General Purpose Image Processing System

 Mass storage capability is a must in image processing

applications.
 An image of size 1024 * 1024 pixels, in which the intensity
of each pixel is an 8-bit quantity, requires one megabyte of
storage space if the image is not compressed.
 Digital storage for image processing applications falls into
three principal categories:
 Short-term storage for use during processing,
 On-line storage for relatively fast recall, and
 Archival storage, characterized by infrequent access.
 Storage is measured in:
 bytes,
 Kbytes,
 Mbytes,
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 Gbytes, and
 General Purpose Image Processing System

 Image displays in use today are mainly color

(preferably flat screen) TV monitors.

 Monitors are driven by the outputs of image and

graphics display cards that are an integral part of the
computer system.

 In some cases, it is necessary to have stereo displays,

and these are implemented in the form of headgear
containing two small displays embedded in goggles
worn by the user.

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 General Purpose Image Processing System

 Hardcopy devices for recording images include laser

printers, film cameras, heat-sensitive devices, inkjet
units, and digital units, such as optical and CDROM
disks.

 Networking is almost a default function in any

computer system in use today.
In dedicated networks, this typically is not a
problem, but communications with remote sites via the
Internet are not always as efficient.

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 Image Processing Basics

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 Image Representation

Pixel

Origin x
(0,0)
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 Image Representation
 A digital image is
composed of M rows
and N columns of
pixels each storing a
value

 Pixel values are most

often grey levels in the
range 0-255(black-
white)

 We will see later on

that images can easily
be represented as
matrices.
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 Image Representation

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 Image Acquisition

 Images are typically

generated by
illuminating a scene
and absorbing the
energy reflected by
the objects in that
scene
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 Image Sensing
 Incoming energy lands on a
sensor material responsive
to that type of energy and
this generates a voltage
 Collections of sensors are
arranged to capture images

Imaging Sensor

Line of Image Sensors

58 Array of Image Sensors

 Image Sampling And Quantization

 A digital sensor can only measure a limited number

of samples at a discrete set of energy levels
 Quantisation is the process of converting a
continuous analogue signal into a digital
representation of this signal
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 Image Sampling And Quantization
 Remember that a digital image is always only an
approximation of a real world scene.

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 Spatial Resolution
 The spatial resolution of an image is determined by
how sampling was carried out
 Spatial resolution simply refers to the smallest
discernable detail in an image
 Vision specialists will often talk about pixel size
 Graphic designers will talk about dots per inch (DPI)

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 Spatial Resolution

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Vision specialists will often talk about pixel
size
 Spatial Resolution
1024 * 1024 512 * 512 256 * 256

128 * 128 64 * 64 32 * 32
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 Intensity Level Resolution
 Intensity level resolution refers to the number 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 of the
number of bits used to store each intensity level

Number of
Number of Bits Examples
Intensity Levels
1 2 0, 1
2 4 00, 01, 10, 11
4 16 0000, 0101, 1111
8 256 00110011,
64 16 65,536 10100110011001100110101
0
 Intensity Level Resolution
256 grey levels (8 bits per pixe1l)28 grey levels (7 bpp) 64 grey levels (6 bpp) 32 grey levels (5 bpp)

65 16 grey levels (4 bpp) 8 grey levels (3 bpp) 4 grey levels (2 bpp) 2 grey levels (1
bpp)
 Resolution: How Much Is Enough?
 The big question with resolution is always how much is
enough?
 This all depends on what is in the image and what 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?

 The picture on the right is fine for counting the

66 number of cars, but not for reading the number plate
Thank You