SlideShare a Scribd company logo
Mr. A. B. Shinde
Assistant Professor,
Electronics Engineering,
P.V.P.I.T., Budhgaon
shindesir.pvp@gmail.com
Digital Image Processing
Fundamentals
1
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.
2
What is Image Processing
3
What is Image Processing
4
What is Image Processing
5
What is Image Processing
One picture is worth more than thousands of words.6
 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
WHY…..digital image processing…???
7
DIP Definition:
A Discipline in Which Both the Input and Output of a
Process are Images.
WHAT IS DIGITAL IMAGE PROCESSING?
ProcessImage Image
8
 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.
What Is Digital Image ?
( , )
( , ) ( , )
( , )
r x y
f x y g x y
b x y
 
 
 
  
The field of digital image processing refers to processing digital
images by means of a digital computer.
 Color Image:
9
An Image:
Discretizatio
n
Quantizatio
n
g(x , y)
g(i , j)
f(i , j) Digital Image
f(i0 , j0) : Picture Element, Image Element, Pel, Pixel
What Is Digital Image ?
10
Image
Processing Vision
Low-Level
Process Mid-Level
Process
High-Level
Process
• Reduce Noise
• Contrast Enhancement
• Image Sharpening
• Segmentation
• Classification
Making Sense of an
Ensemble of
Recognized Objects
Image Analysis
WHAT IS DIGITAL IMAGE PROCESSING?
11
 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.
Origins of Digital Image Processing
A digital picture produced in
1921 from a coded tape by a
telegraph printer with special
type faces.
12
 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
Fields that Use Digital Image Processing
13
Gamma-Ray Imaging
 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.
Bone scan PET
Cygnus loop Reactor valve14
X-Ray Imaging
Cygnus loop
PCB
Chest
X-Ray
Head CT
Angiogram
15
Applications and Research Topics
16
 Document Handling
Applications and Research Topics
17
 Signature Verification
Applications and Research Topics
18
 Biometrics
Applications and Research Topics
19
 Fingerprint Verification / Identification
Applications and Research Topics
20
 Object Recognition
Applications and Research Topics
21
 Target Recognition
Department of Defense (Army, Air force, Navy)
Applications and Research Topics
22
 Interpretation of Aerial Photography
Interpretation of aerial photography is a problem domain in both
computer vision and registration.
Applications and Research Topics
23
 Autonomous Vehicles
Land, Underwater, Space
Applications and Research Topics
24
 Traffic Monitoring
Applications and Research Topics
25
 Traffic Monitoring
Applications and Research Topics
26
 Face Detection
Applications and Research Topics
27
 Face Recognition
Applications and Research Topics
28
 Face Detection/Recognition Research
Applications and Research Topics
29
 Facial Expression Recognition
Applications and Research Topics
30
 Hand Gesture Recognition
Smart Human-Computer User Interfaces
Sign Language Recognition
Applications and Research Topics
31
 Human Activity Recognition
Applications and Research Topics
32
 Medical Applications
Applications and Research Topics
breast cancerskin cancer
33
 Morphing
Applications and Research Topics
34
 Inserting Artificial Objects into a Scene
Applications and Research Topics
35
Fundamental Steps in Digital Image Processing
36
Fundamental Steps in Digital Image Processing
37
Fundamental Steps in Digital Image Processing
Essential steps when processing digital images:
Acquisition
Enhancement
Restoration
Color image restoration
Wavelets
Morphological processing
Segmentation
Representation
Recognition
Outputs are
digital
images
Outputs are
attributes of the
image
38
Fundamental Steps in Digital Image Processing
 Image acquisition is the first process.
Generally, the image acquisition stage involves
preprocessing, such as scaling.
39
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.
40
 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.
Fundamental Steps in Digital Image Processing
41
 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.
Fundamental Steps in Digital Image Processing
42
 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.
Fundamental Steps in Digital Image Processing
43
 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.
Fundamental Steps in Digital Image Processing
44
 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.
Fundamental Steps in Digital Image Processing
45
General Purpose Image Processing System
46
 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.
General Purpose Image Processing System
47
 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.
General Purpose Image Processing System
48
 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.
General Purpose Image Processing System
49
 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,
 Gbytes, and
General Purpose Image Processing System
50
 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.
General Purpose Image Processing System
51
 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.
General Purpose Image Processing System
52
Image Processing Basics
53
Image Representation
54
x
y
Origin
(0,0)
Pixel
 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.
Image Representation
55
Image Representation
56
 Images are typically
generated by
illuminating a scene
and absorbing the
energy reflected by
the objects in that
scene
Image Acquisition
57
 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
Image Sensing
Imaging Sensor
Line of Image Sensors
Array of Image Sensors58
 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
Image Sampling And Quantization
59
 Remember that a digital image is always only an
approximation of a real world scene.
Image Sampling And Quantization
60
 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)
Spatial Resolution
61
Spatial Resolution
Vision specialists will often talk about pixel
size
62
Spatial Resolution
1024 * 1024 512 * 512 256 * 256
128 * 128 64 * 64 32 * 32
Graphic designers will talk about dots per inch63
 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
Intensity Level Resolution
Number of Bits
Number of
Intensity Levels
Examples
1 2 0, 1
2 4 00, 01, 10, 11
4 16 0000, 0101, 1111
8 256 00110011,
0101010116 65,536 101010101010101
0
64
Intensity Level Resolution
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)
65
 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?
Resolution: How Much Is Enough?
 The picture on the right is fine for counting the
number of cars, but not for reading the number plate66
Thank You…
(This Presentation is Published Only for Educational Purpose)
67

More Related Content

What's hot

image compression ppt
image compression pptimage compression ppt
image compression ppt
Shivangi Saxena
 
Image Restoration
Image RestorationImage Restoration
Image Restoration
Poonam Seth
 
Image Restoration (Digital Image Processing)
Image Restoration (Digital Image Processing)Image Restoration (Digital Image Processing)
Image Restoration (Digital Image Processing)
Kalyan Acharjya
 
Digital image processing
Digital image processingDigital image processing
Digital image processing
manpreetgrewal
 
Lecture 1 for Digital Image Processing (2nd Edition)
Lecture 1 for Digital Image Processing (2nd Edition)Lecture 1 for Digital Image Processing (2nd Edition)
Lecture 1 for Digital Image Processing (2nd Edition)
Moe Moe Myint
 
Fundamentals steps in Digital Image processing
Fundamentals steps in Digital Image processingFundamentals steps in Digital Image processing
Fundamentals steps in Digital Image processing
KarthicaMarasamy
 
Image segmentation ppt
Image segmentation pptImage segmentation ppt
Image segmentation ppt
Gichelle Amon
 
digital image processing
digital image processingdigital image processing
digital image processing
Abinaya B
 
Digital Image Processing (DIP)
Digital Image Processing (DIP)Digital Image Processing (DIP)
Digital Image Processing (DIP)
Srikanth VNV
 
Fundamental Steps of Digital Image Processing & Image Components
Fundamental Steps of Digital Image Processing & Image ComponentsFundamental Steps of Digital Image Processing & Image Components
Fundamental Steps of Digital Image Processing & Image Components
Kalyan Acharjya
 
Image Processing: Spatial filters
Image Processing: Spatial filtersImage Processing: Spatial filters
Image Processing: Spatial filters
A B Shinde
 
Color fundamentals and color models - Digital Image Processing
Color fundamentals and color models - Digital Image ProcessingColor fundamentals and color models - Digital Image Processing
Color fundamentals and color models - Digital Image Processing
Amna
 
digital image processing
digital image processingdigital image processing
digital image processing
N.CH Karthik
 
Image Enhancement in Spatial Domain
Image Enhancement in Spatial DomainImage Enhancement in Spatial Domain
Image Enhancement in Spatial Domain
A B Shinde
 
Digital Image Processing: An Introduction
Digital Image Processing: An IntroductionDigital Image Processing: An Introduction
Digital Image Processing: An Introduction
Mostafa G. M. Mostafa
 
Image segmentation
Image segmentationImage segmentation
Image segmentation
Md Shabir Alam
 
Image Enhancement in Spatial Domain
Image Enhancement in Spatial DomainImage Enhancement in Spatial Domain
Image Enhancement in Spatial Domain
DEEPASHRI HK
 
Image processing
Image processingImage processing
Image processing
Raga Deepthi
 
Image segmentation
Image segmentation Image segmentation
Image Processing
Image ProcessingImage Processing
Image Processing
Rolando
 

What's hot (20)

image compression ppt
image compression pptimage compression ppt
image compression ppt
 
Image Restoration
Image RestorationImage Restoration
Image Restoration
 
Image Restoration (Digital Image Processing)
Image Restoration (Digital Image Processing)Image Restoration (Digital Image Processing)
Image Restoration (Digital Image Processing)
 
Digital image processing
Digital image processingDigital image processing
Digital image processing
 
Lecture 1 for Digital Image Processing (2nd Edition)
Lecture 1 for Digital Image Processing (2nd Edition)Lecture 1 for Digital Image Processing (2nd Edition)
Lecture 1 for Digital Image Processing (2nd Edition)
 
Fundamentals steps in Digital Image processing
Fundamentals steps in Digital Image processingFundamentals steps in Digital Image processing
Fundamentals steps in Digital Image processing
 
Image segmentation ppt
Image segmentation pptImage segmentation ppt
Image segmentation ppt
 
digital image processing
digital image processingdigital image processing
digital image processing
 
Digital Image Processing (DIP)
Digital Image Processing (DIP)Digital Image Processing (DIP)
Digital Image Processing (DIP)
 
Fundamental Steps of Digital Image Processing & Image Components
Fundamental Steps of Digital Image Processing & Image ComponentsFundamental Steps of Digital Image Processing & Image Components
Fundamental Steps of Digital Image Processing & Image Components
 
Image Processing: Spatial filters
Image Processing: Spatial filtersImage Processing: Spatial filters
Image Processing: Spatial filters
 
Color fundamentals and color models - Digital Image Processing
Color fundamentals and color models - Digital Image ProcessingColor fundamentals and color models - Digital Image Processing
Color fundamentals and color models - Digital Image Processing
 
digital image processing
digital image processingdigital image processing
digital image processing
 
Image Enhancement in Spatial Domain
Image Enhancement in Spatial DomainImage Enhancement in Spatial Domain
Image Enhancement in Spatial Domain
 
Digital Image Processing: An Introduction
Digital Image Processing: An IntroductionDigital Image Processing: An Introduction
Digital Image Processing: An Introduction
 
Image segmentation
Image segmentationImage segmentation
Image segmentation
 
Image Enhancement in Spatial Domain
Image Enhancement in Spatial DomainImage Enhancement in Spatial Domain
Image Enhancement in Spatial Domain
 
Image processing
Image processingImage processing
Image processing
 
Image segmentation
Image segmentation Image segmentation
Image segmentation
 
Image Processing
Image ProcessingImage Processing
Image Processing
 

Similar to Image processing fundamentals

ch-1.1 image processing fundamentals.pptx
ch-1.1 image processing fundamentals.pptxch-1.1 image processing fundamentals.pptx
ch-1.1 image processing fundamentals.pptx
satyanarayana242612
 
Unit 1 DIP Fundamentals - Presentation Notes.pdf
Unit 1 DIP Fundamentals - Presentation Notes.pdfUnit 1 DIP Fundamentals - Presentation Notes.pdf
Unit 1 DIP Fundamentals - Presentation Notes.pdf
sdbhosale860
 
Digital_image_processing_-Vijaya_Raghavan.pdf
Digital_image_processing_-Vijaya_Raghavan.pdfDigital_image_processing_-Vijaya_Raghavan.pdf
Digital_image_processing_-Vijaya_Raghavan.pdf
VaideshSiva1
 
A Review on Overview of Image Processing Techniques
A Review on Overview of Image Processing TechniquesA Review on Overview of Image Processing Techniques
A Review on Overview of Image Processing Techniques
ijtsrd
 
Digital image processing using matlab
Digital image processing using matlab Digital image processing using matlab
Digital image processing using matlab
Amr Rashed
 
Image Processing in the Current Scenario
Image Processing in the Current ScenarioImage Processing in the Current Scenario
Image Processing in the Current Scenario
ijtsrd
 
B tech vi sem cse dip lecture 1
B tech vi sem cse dip  lecture 1B tech vi sem cse dip  lecture 1
B tech vi sem cse dip lecture 1
himanshu swarnkar
 
DIP-LECTURE_NOTES.pdf
DIP-LECTURE_NOTES.pdfDIP-LECTURE_NOTES.pdf
DIP-LECTURE_NOTES.pdf
VaideshSiva1
 
Dip
DipDip
image Processing Fundamental Is .ppt
image Processing Fundamental Is     .pptimage Processing Fundamental Is     .ppt
image Processing Fundamental Is .ppt
Desalechali1
 
Image Processing Fundamentals .ppt
Image Processing Fundamentals        .pptImage Processing Fundamentals        .ppt
Image Processing Fundamentals .ppt
Desalechali1
 
EC4160-lect 1,2.ppt
EC4160-lect 1,2.pptEC4160-lect 1,2.ppt
EC4160-lect 1,2.ppt
ssuser812128
 
A review on image processing
A review on image processingA review on image processing
A review on image processing
Alexander Decker
 
Evaluation Of Proposed Design And Necessary Corrective Action
Evaluation Of Proposed Design And Necessary Corrective ActionEvaluation Of Proposed Design And Necessary Corrective Action
Evaluation Of Proposed Design And Necessary Corrective Action
Sandra Arveseth
 
Image Processing By SAIKIRAN PANJALA
 Image Processing By SAIKIRAN PANJALA Image Processing By SAIKIRAN PANJALA
Image Processing By SAIKIRAN PANJALA
Saikiran Panjala
 
Ch1.pptx
Ch1.pptxCh1.pptx
Ch1.pptx
danielzewde12
 
Lec_1_Introduction.pdf
Lec_1_Introduction.pdfLec_1_Introduction.pdf
Lec_1_Introduction.pdf
nagwaAboElenein
 
Lec_1_Introduction.pdf
Lec_1_Introduction.pdfLec_1_Introduction.pdf
Lec_1_Introduction.pdf
nagwaAboElenein
 
Jc3416551658
Jc3416551658Jc3416551658
Jc3416551658
IJERA Editor
 
Review Paper on Image Processing Techniques
Review Paper on Image Processing TechniquesReview Paper on Image Processing Techniques
Review Paper on Image Processing Techniques
IJSRD
 

Similar to Image processing fundamentals (20)

ch-1.1 image processing fundamentals.pptx
ch-1.1 image processing fundamentals.pptxch-1.1 image processing fundamentals.pptx
ch-1.1 image processing fundamentals.pptx
 
Unit 1 DIP Fundamentals - Presentation Notes.pdf
Unit 1 DIP Fundamentals - Presentation Notes.pdfUnit 1 DIP Fundamentals - Presentation Notes.pdf
Unit 1 DIP Fundamentals - Presentation Notes.pdf
 
Digital_image_processing_-Vijaya_Raghavan.pdf
Digital_image_processing_-Vijaya_Raghavan.pdfDigital_image_processing_-Vijaya_Raghavan.pdf
Digital_image_processing_-Vijaya_Raghavan.pdf
 
A Review on Overview of Image Processing Techniques
A Review on Overview of Image Processing TechniquesA Review on Overview of Image Processing Techniques
A Review on Overview of Image Processing Techniques
 
Digital image processing using matlab
Digital image processing using matlab Digital image processing using matlab
Digital image processing using matlab
 
Image Processing in the Current Scenario
Image Processing in the Current ScenarioImage Processing in the Current Scenario
Image Processing in the Current Scenario
 
B tech vi sem cse dip lecture 1
B tech vi sem cse dip  lecture 1B tech vi sem cse dip  lecture 1
B tech vi sem cse dip lecture 1
 
DIP-LECTURE_NOTES.pdf
DIP-LECTURE_NOTES.pdfDIP-LECTURE_NOTES.pdf
DIP-LECTURE_NOTES.pdf
 
Dip
DipDip
Dip
 
image Processing Fundamental Is .ppt
image Processing Fundamental Is     .pptimage Processing Fundamental Is     .ppt
image Processing Fundamental Is .ppt
 
Image Processing Fundamentals .ppt
Image Processing Fundamentals        .pptImage Processing Fundamentals        .ppt
Image Processing Fundamentals .ppt
 
EC4160-lect 1,2.ppt
EC4160-lect 1,2.pptEC4160-lect 1,2.ppt
EC4160-lect 1,2.ppt
 
A review on image processing
A review on image processingA review on image processing
A review on image processing
 
Evaluation Of Proposed Design And Necessary Corrective Action
Evaluation Of Proposed Design And Necessary Corrective ActionEvaluation Of Proposed Design And Necessary Corrective Action
Evaluation Of Proposed Design And Necessary Corrective Action
 
Image Processing By SAIKIRAN PANJALA
 Image Processing By SAIKIRAN PANJALA Image Processing By SAIKIRAN PANJALA
Image Processing By SAIKIRAN PANJALA
 
Ch1.pptx
Ch1.pptxCh1.pptx
Ch1.pptx
 
Lec_1_Introduction.pdf
Lec_1_Introduction.pdfLec_1_Introduction.pdf
Lec_1_Introduction.pdf
 
Lec_1_Introduction.pdf
Lec_1_Introduction.pdfLec_1_Introduction.pdf
Lec_1_Introduction.pdf
 
Jc3416551658
Jc3416551658Jc3416551658
Jc3416551658
 
Review Paper on Image Processing Techniques
Review Paper on Image Processing TechniquesReview Paper on Image Processing Techniques
Review Paper on Image Processing Techniques
 

More from A B Shinde

Communication System Basics
Communication System BasicsCommunication System Basics
Communication System Basics
A B Shinde
 
MOSFETs: Single Stage IC Amplifier
MOSFETs: Single Stage IC AmplifierMOSFETs: Single Stage IC Amplifier
MOSFETs: Single Stage IC Amplifier
A B Shinde
 
MOSFETs
MOSFETsMOSFETs
MOSFETs
A B Shinde
 
Color Image Processing: Basics
Color Image Processing: BasicsColor Image Processing: Basics
Color Image Processing: Basics
A B Shinde
 
Edge Detection and Segmentation
Edge Detection and SegmentationEdge Detection and Segmentation
Edge Detection and Segmentation
A B Shinde
 
Resume Format
Resume FormatResume Format
Resume Format
A B Shinde
 
Digital Image Fundamentals
Digital Image FundamentalsDigital Image Fundamentals
Digital Image Fundamentals
A B Shinde
 
Resume Writing
Resume WritingResume Writing
Resume Writing
A B Shinde
 
Blooms Taxonomy in Engineering Education
Blooms Taxonomy in Engineering EducationBlooms Taxonomy in Engineering Education
Blooms Taxonomy in Engineering Education
A B Shinde
 
ISE 7.1i Software
ISE 7.1i SoftwareISE 7.1i Software
ISE 7.1i Software
A B Shinde
 
VHDL Coding Syntax
VHDL Coding SyntaxVHDL Coding Syntax
VHDL Coding Syntax
A B Shinde
 
VHDL Programs
VHDL ProgramsVHDL Programs
VHDL Programs
A B Shinde
 
VLSI Testing Techniques
VLSI Testing TechniquesVLSI Testing Techniques
VLSI Testing Techniques
A B Shinde
 
Selecting Engineering Project
Selecting Engineering ProjectSelecting Engineering Project
Selecting Engineering Project
A B Shinde
 
Interview Techniques
Interview TechniquesInterview Techniques
Interview Techniques
A B Shinde
 
Semiconductors
SemiconductorsSemiconductors
Semiconductors
A B Shinde
 
Diode Applications & Transistor Basics
Diode Applications & Transistor BasicsDiode Applications & Transistor Basics
Diode Applications & Transistor Basics
A B Shinde
 
Electronics Basic Concepts
Electronics Basic ConceptsElectronics Basic Concepts
Electronics Basic Concepts
A B Shinde
 
Multithreading
MultithreadingMultithreading
Multithreading
A B Shinde
 
Multiprocessor
MultiprocessorMultiprocessor
Multiprocessor
A B Shinde
 

More from A B Shinde (20)

Communication System Basics
Communication System BasicsCommunication System Basics
Communication System Basics
 
MOSFETs: Single Stage IC Amplifier
MOSFETs: Single Stage IC AmplifierMOSFETs: Single Stage IC Amplifier
MOSFETs: Single Stage IC Amplifier
 
MOSFETs
MOSFETsMOSFETs
MOSFETs
 
Color Image Processing: Basics
Color Image Processing: BasicsColor Image Processing: Basics
Color Image Processing: Basics
 
Edge Detection and Segmentation
Edge Detection and SegmentationEdge Detection and Segmentation
Edge Detection and Segmentation
 
Resume Format
Resume FormatResume Format
Resume Format
 
Digital Image Fundamentals
Digital Image FundamentalsDigital Image Fundamentals
Digital Image Fundamentals
 
Resume Writing
Resume WritingResume Writing
Resume Writing
 
Blooms Taxonomy in Engineering Education
Blooms Taxonomy in Engineering EducationBlooms Taxonomy in Engineering Education
Blooms Taxonomy in Engineering Education
 
ISE 7.1i Software
ISE 7.1i SoftwareISE 7.1i Software
ISE 7.1i Software
 
VHDL Coding Syntax
VHDL Coding SyntaxVHDL Coding Syntax
VHDL Coding Syntax
 
VHDL Programs
VHDL ProgramsVHDL Programs
VHDL Programs
 
VLSI Testing Techniques
VLSI Testing TechniquesVLSI Testing Techniques
VLSI Testing Techniques
 
Selecting Engineering Project
Selecting Engineering ProjectSelecting Engineering Project
Selecting Engineering Project
 
Interview Techniques
Interview TechniquesInterview Techniques
Interview Techniques
 
Semiconductors
SemiconductorsSemiconductors
Semiconductors
 
Diode Applications & Transistor Basics
Diode Applications & Transistor BasicsDiode Applications & Transistor Basics
Diode Applications & Transistor Basics
 
Electronics Basic Concepts
Electronics Basic ConceptsElectronics Basic Concepts
Electronics Basic Concepts
 
Multithreading
MultithreadingMultithreading
Multithreading
 
Multiprocessor
MultiprocessorMultiprocessor
Multiprocessor
 

Recently uploaded

LOCAL-BUDGET-CIRCULAR-NO-158-DATED-JULY-11-2024.pdf
LOCAL-BUDGET-CIRCULAR-NO-158-DATED-JULY-11-2024.pdfLOCAL-BUDGET-CIRCULAR-NO-158-DATED-JULY-11-2024.pdf
LOCAL-BUDGET-CIRCULAR-NO-158-DATED-JULY-11-2024.pdf
jellyjm
 
Time-State Analytics: MinneAnalytics 2024 Talk
Time-State Analytics: MinneAnalytics 2024 TalkTime-State Analytics: MinneAnalytics 2024 Talk
Time-State Analytics: MinneAnalytics 2024 Talk
Evan Chan
 
Traffic Engineering-MODULE-1 vtu syllabus.pptx
Traffic Engineering-MODULE-1 vtu syllabus.pptxTraffic Engineering-MODULE-1 vtu syllabus.pptx
Traffic Engineering-MODULE-1 vtu syllabus.pptx
mailmad391
 
Probability and Statistics by sheldon ross (8th edition).pdf
Probability and Statistics by sheldon ross (8th edition).pdfProbability and Statistics by sheldon ross (8th edition).pdf
Probability and Statistics by sheldon ross (8th edition).pdf
utkarshakusnake
 
Girls Call Chennai 000XX00000 Provide Best And Top Girl Service And No1 in City
Girls Call Chennai 000XX00000 Provide Best And Top Girl Service And No1 in CityGirls Call Chennai 000XX00000 Provide Best And Top Girl Service And No1 in City
Girls Call Chennai 000XX00000 Provide Best And Top Girl Service And No1 in City
sunnuchadda
 
Girls Call Mysore 000XX00000 Provide Best And Top Girl Service And No1 in City
Girls Call Mysore 000XX00000 Provide Best And Top Girl Service And No1 in CityGirls Call Mysore 000XX00000 Provide Best And Top Girl Service And No1 in City
Girls Call Mysore 000XX00000 Provide Best And Top Girl Service And No1 in City
rawankhanlove256
 
AI INTRODUCTION Artificial intelligence.ppt
AI INTRODUCTION Artificial intelligence.pptAI INTRODUCTION Artificial intelligence.ppt
AI INTRODUCTION Artificial intelligence.ppt
GeethaAL
 
charting the development of the autonomous train
charting the development of the autonomous traincharting the development of the autonomous train
charting the development of the autonomous train
huseindihon
 
If we're running two pumps, why aren't we getting twice as much flow? v.17
If we're running two pumps, why aren't we getting twice as much flow? v.17If we're running two pumps, why aren't we getting twice as much flow? v.17
If we're running two pumps, why aren't we getting twice as much flow? v.17
Brian Gongol
 
IE-469-Lecture-Notes-3IE-469-Lecture-Notes-3.pptx
IE-469-Lecture-Notes-3IE-469-Lecture-Notes-3.pptxIE-469-Lecture-Notes-3IE-469-Lecture-Notes-3.pptx
IE-469-Lecture-Notes-3IE-469-Lecture-Notes-3.pptx
BehairyAhmed2
 
How to Formulate A Good Research Question
How to Formulate A  Good Research QuestionHow to Formulate A  Good Research Question
How to Formulate A Good Research Question
rkpv2002
 
EAAP2023 : Durabilité et services écosystémiques de l'élevage ovin de montagne
EAAP2023 : Durabilité et services écosystémiques de l'élevage ovin de montagneEAAP2023 : Durabilité et services écosystémiques de l'élevage ovin de montagne
EAAP2023 : Durabilité et services écosystémiques de l'élevage ovin de montagne
idelewebmestre
 
Smart Factory – Starter Engagement Design.pptx
Smart Factory – Starter Engagement Design.pptxSmart Factory – Starter Engagement Design.pptx
Smart Factory – Starter Engagement Design.pptx
longngoai00
 
The Control of Relative Humidity & Moisture Content in The Air
The Control of Relative Humidity & Moisture Content in The AirThe Control of Relative Humidity & Moisture Content in The Air
The Control of Relative Humidity & Moisture Content in The Air
Ashraf Ismail
 
Distillation-1.vapour liquid equilibrium
Distillation-1.vapour liquid equilibriumDistillation-1.vapour liquid equilibrium
Distillation-1.vapour liquid equilibrium
RjKing12
 
杨洋李一桐做爱视频流出【网芷:ht28.co】国产国产午夜精华>>>[网趾:ht28.co】]<<<
杨洋李一桐做爱视频流出【网芷:ht28.co】国产国产午夜精华>>>[网趾:ht28.co】]<<<杨洋李一桐做爱视频流出【网芷:ht28.co】国产国产午夜精华>>>[网趾:ht28.co】]<<<
杨洋李一桐做爱视频流出【网芷:ht28.co】国产国产午夜精华>>>[网趾:ht28.co】]<<<
amzhoxvzidbke
 
Sustainable construction is the use of renewable and recyclable materials in ...
Sustainable construction is the use of renewable and recyclable materials in ...Sustainable construction is the use of renewable and recyclable materials in ...
Sustainable construction is the use of renewable and recyclable materials in ...
RohitGhulanavar2
 
AI chapter1 introduction to artificial intelligence
AI chapter1 introduction to artificial intelligenceAI chapter1 introduction to artificial intelligence
AI chapter1 introduction to artificial intelligence
GeethaAL
 
carpentry-11-module-1.docx 1 identifying tools
carpentry-11-module-1.docx 1 identifying toolscarpentry-11-module-1.docx 1 identifying tools
carpentry-11-module-1.docx 1 identifying tools
ChristopherAltizen2
 
Presentation python programming vtu 6th sem
Presentation python programming vtu 6th semPresentation python programming vtu 6th sem
Presentation python programming vtu 6th sem
ssuser8f6b1d1
 

Recently uploaded (20)

LOCAL-BUDGET-CIRCULAR-NO-158-DATED-JULY-11-2024.pdf
LOCAL-BUDGET-CIRCULAR-NO-158-DATED-JULY-11-2024.pdfLOCAL-BUDGET-CIRCULAR-NO-158-DATED-JULY-11-2024.pdf
LOCAL-BUDGET-CIRCULAR-NO-158-DATED-JULY-11-2024.pdf
 
Time-State Analytics: MinneAnalytics 2024 Talk
Time-State Analytics: MinneAnalytics 2024 TalkTime-State Analytics: MinneAnalytics 2024 Talk
Time-State Analytics: MinneAnalytics 2024 Talk
 
Traffic Engineering-MODULE-1 vtu syllabus.pptx
Traffic Engineering-MODULE-1 vtu syllabus.pptxTraffic Engineering-MODULE-1 vtu syllabus.pptx
Traffic Engineering-MODULE-1 vtu syllabus.pptx
 
Probability and Statistics by sheldon ross (8th edition).pdf
Probability and Statistics by sheldon ross (8th edition).pdfProbability and Statistics by sheldon ross (8th edition).pdf
Probability and Statistics by sheldon ross (8th edition).pdf
 
Girls Call Chennai 000XX00000 Provide Best And Top Girl Service And No1 in City
Girls Call Chennai 000XX00000 Provide Best And Top Girl Service And No1 in CityGirls Call Chennai 000XX00000 Provide Best And Top Girl Service And No1 in City
Girls Call Chennai 000XX00000 Provide Best And Top Girl Service And No1 in City
 
Girls Call Mysore 000XX00000 Provide Best And Top Girl Service And No1 in City
Girls Call Mysore 000XX00000 Provide Best And Top Girl Service And No1 in CityGirls Call Mysore 000XX00000 Provide Best And Top Girl Service And No1 in City
Girls Call Mysore 000XX00000 Provide Best And Top Girl Service And No1 in City
 
AI INTRODUCTION Artificial intelligence.ppt
AI INTRODUCTION Artificial intelligence.pptAI INTRODUCTION Artificial intelligence.ppt
AI INTRODUCTION Artificial intelligence.ppt
 
charting the development of the autonomous train
charting the development of the autonomous traincharting the development of the autonomous train
charting the development of the autonomous train
 
If we're running two pumps, why aren't we getting twice as much flow? v.17
If we're running two pumps, why aren't we getting twice as much flow? v.17If we're running two pumps, why aren't we getting twice as much flow? v.17
If we're running two pumps, why aren't we getting twice as much flow? v.17
 
IE-469-Lecture-Notes-3IE-469-Lecture-Notes-3.pptx
IE-469-Lecture-Notes-3IE-469-Lecture-Notes-3.pptxIE-469-Lecture-Notes-3IE-469-Lecture-Notes-3.pptx
IE-469-Lecture-Notes-3IE-469-Lecture-Notes-3.pptx
 
How to Formulate A Good Research Question
How to Formulate A  Good Research QuestionHow to Formulate A  Good Research Question
How to Formulate A Good Research Question
 
EAAP2023 : Durabilité et services écosystémiques de l'élevage ovin de montagne
EAAP2023 : Durabilité et services écosystémiques de l'élevage ovin de montagneEAAP2023 : Durabilité et services écosystémiques de l'élevage ovin de montagne
EAAP2023 : Durabilité et services écosystémiques de l'élevage ovin de montagne
 
Smart Factory – Starter Engagement Design.pptx
Smart Factory – Starter Engagement Design.pptxSmart Factory – Starter Engagement Design.pptx
Smart Factory – Starter Engagement Design.pptx
 
The Control of Relative Humidity & Moisture Content in The Air
The Control of Relative Humidity & Moisture Content in The AirThe Control of Relative Humidity & Moisture Content in The Air
The Control of Relative Humidity & Moisture Content in The Air
 
Distillation-1.vapour liquid equilibrium
Distillation-1.vapour liquid equilibriumDistillation-1.vapour liquid equilibrium
Distillation-1.vapour liquid equilibrium
 
杨洋李一桐做爱视频流出【网芷:ht28.co】国产国产午夜精华>>>[网趾:ht28.co】]<<<
杨洋李一桐做爱视频流出【网芷:ht28.co】国产国产午夜精华>>>[网趾:ht28.co】]<<<杨洋李一桐做爱视频流出【网芷:ht28.co】国产国产午夜精华>>>[网趾:ht28.co】]<<<
杨洋李一桐做爱视频流出【网芷:ht28.co】国产国产午夜精华>>>[网趾:ht28.co】]<<<
 
Sustainable construction is the use of renewable and recyclable materials in ...
Sustainable construction is the use of renewable and recyclable materials in ...Sustainable construction is the use of renewable and recyclable materials in ...
Sustainable construction is the use of renewable and recyclable materials in ...
 
AI chapter1 introduction to artificial intelligence
AI chapter1 introduction to artificial intelligenceAI chapter1 introduction to artificial intelligence
AI chapter1 introduction to artificial intelligence
 
carpentry-11-module-1.docx 1 identifying tools
carpentry-11-module-1.docx 1 identifying toolscarpentry-11-module-1.docx 1 identifying tools
carpentry-11-module-1.docx 1 identifying tools
 
Presentation python programming vtu 6th sem
Presentation python programming vtu 6th semPresentation python programming vtu 6th sem
Presentation python programming vtu 6th sem
 

Image processing fundamentals

  • 1. Mr. A. B. Shinde Assistant Professor, Electronics Engineering, P.V.P.I.T., Budhgaon shindesir.pvp@gmail.com Digital Image Processing Fundamentals 1
  • 2. 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. 2
  • 3. What is Image Processing 3
  • 4. What is Image Processing 4
  • 5. What is Image Processing 5
  • 6. What is Image Processing One picture is worth more than thousands of words.6
  • 7.  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 WHY…..digital image processing…??? 7
  • 8. DIP Definition: A Discipline in Which Both the Input and Output of a Process are Images. WHAT IS DIGITAL IMAGE PROCESSING? ProcessImage Image 8
  • 9.  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. What Is Digital Image ? ( , ) ( , ) ( , ) ( , ) r x y f x y g x y b x y          The field of digital image processing refers to processing digital images by means of a digital computer.  Color Image: 9
  • 10. An Image: Discretizatio n Quantizatio n g(x , y) g(i , j) f(i , j) Digital Image f(i0 , j0) : Picture Element, Image Element, Pel, Pixel What Is Digital Image ? 10
  • 11. Image Processing Vision Low-Level Process Mid-Level Process High-Level Process • Reduce Noise • Contrast Enhancement • Image Sharpening • Segmentation • Classification Making Sense of an Ensemble of Recognized Objects Image Analysis WHAT IS DIGITAL IMAGE PROCESSING? 11
  • 12.  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. Origins of Digital Image Processing A digital picture produced in 1921 from a coded tape by a telegraph printer with special type faces. 12
  • 13.  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 Fields that Use Digital Image Processing 13
  • 14. Gamma-Ray Imaging  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. Bone scan PET Cygnus loop Reactor valve14
  • 17.  Document Handling Applications and Research Topics 17
  • 18.  Signature Verification Applications and Research Topics 18
  • 19.  Biometrics Applications and Research Topics 19
  • 20.  Fingerprint Verification / Identification Applications and Research Topics 20
  • 21.  Object Recognition Applications and Research Topics 21
  • 22.  Target Recognition Department of Defense (Army, Air force, Navy) Applications and Research Topics 22
  • 23.  Interpretation of Aerial Photography Interpretation of aerial photography is a problem domain in both computer vision and registration. Applications and Research Topics 23
  • 24.  Autonomous Vehicles Land, Underwater, Space Applications and Research Topics 24
  • 25.  Traffic Monitoring Applications and Research Topics 25
  • 26.  Traffic Monitoring Applications and Research Topics 26
  • 27.  Face Detection Applications and Research Topics 27
  • 28.  Face Recognition Applications and Research Topics 28
  • 29.  Face Detection/Recognition Research Applications and Research Topics 29
  • 30.  Facial Expression Recognition Applications and Research Topics 30
  • 31.  Hand Gesture Recognition Smart Human-Computer User Interfaces Sign Language Recognition Applications and Research Topics 31
  • 32.  Human Activity Recognition Applications and Research Topics 32
  • 33.  Medical Applications Applications and Research Topics breast cancerskin cancer 33
  • 34.  Morphing Applications and Research Topics 34
  • 35.  Inserting Artificial Objects into a Scene Applications and Research Topics 35
  • 36. Fundamental Steps in Digital Image Processing 36
  • 37. Fundamental Steps in Digital Image Processing 37
  • 38. Fundamental Steps in Digital Image Processing Essential steps when processing digital images: Acquisition Enhancement Restoration Color image restoration Wavelets Morphological processing Segmentation Representation Recognition Outputs are digital images Outputs are attributes of the image 38
  • 39. Fundamental Steps in Digital Image Processing  Image acquisition is the first process. Generally, the image acquisition stage involves preprocessing, such as scaling. 39
  • 40. 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. 40
  • 41.  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. Fundamental Steps in Digital Image Processing 41
  • 42.  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. Fundamental Steps in Digital Image Processing 42
  • 43.  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. Fundamental Steps in Digital Image Processing 43
  • 44.  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. Fundamental Steps in Digital Image Processing 44
  • 45.  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. Fundamental Steps in Digital Image Processing 45
  • 46. General Purpose Image Processing System 46
  • 47.  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. General Purpose Image Processing System 47
  • 48.  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. General Purpose Image Processing System 48
  • 49.  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. General Purpose Image Processing System 49
  • 50.  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,  Gbytes, and General Purpose Image Processing System 50
  • 51.  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. General Purpose Image Processing System 51
  • 52.  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. General Purpose Image Processing System 52
  • 55.  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. Image Representation 55
  • 57.  Images are typically generated by illuminating a scene and absorbing the energy reflected by the objects in that scene Image Acquisition 57
  • 58.  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 Image Sensing Imaging Sensor Line of Image Sensors Array of Image Sensors58
  • 59.  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 Image Sampling And Quantization 59
  • 60.  Remember that a digital image is always only an approximation of a real world scene. Image Sampling And Quantization 60
  • 61.  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) Spatial Resolution 61
  • 62. Spatial Resolution Vision specialists will often talk about pixel size 62
  • 63. Spatial Resolution 1024 * 1024 512 * 512 256 * 256 128 * 128 64 * 64 32 * 32 Graphic designers will talk about dots per inch63
  • 64.  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 Intensity Level Resolution Number of Bits Number of Intensity Levels Examples 1 2 0, 1 2 4 00, 01, 10, 11 4 16 0000, 0101, 1111 8 256 00110011, 0101010116 65,536 101010101010101 0 64
  • 65. Intensity Level Resolution 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) 65
  • 66.  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? Resolution: How Much Is Enough?  The picture on the right is fine for counting the number of cars, but not for reading the number plate66
  • 67. Thank You… (This Presentation is Published Only for Educational Purpose) 67