SlideShare une entreprise Scribd logo
1  sur  17
CLASS -2
FUNDAMENTAL STEPS IN DIGITAL IMAGE
PROCESSING
• There is no general “theory” of image enhancement .When an image is
processed for visual interpretation.
• Enhancement techniques are so varied and use so many different image
processing approaches.
• Difficult to assemble a meaningful body of techniques suitable for
enhancement in one chapter without extensive background development.
• Beginners in the field of image processing generally find enhancement
applications visually appealing , interesting and relatively simple to
understand.
IMAGE ACQUISITION
• It is defined as the action of retrieving an image from some source,
usually a hardware source of processing.
• The image that is required is completely unprocessed.
IMAGE ENHANCEMENT
• It is widely used in computer graphics.
• The objectives of image enhancement techniques is to process an
image so that the result is more suitable than the original image for a
specific application.
MK(13/07/2020)
COLOR IMAGE PROCESSING
• It is an area that has been gaining in importance because of the significant
increase in the use of digital images over the internet.
• Color is used also in later chapter as the basics for extracting features of interest
in an image.
WAVELETS AND MULTIRESOLUTION
PROCESSING
• It is foundation for representing images in various degrees of
resolution.
• In data compression & for pyramidal representation in which images
are subdivided successively into smaller regions.
IMAGE REPRESENTATION & DESCRIPTION
• After the image is segmented into regions, the resulting aggregate of
segmented pixels is represented & described for further computer
processing.
• Representation in two ways :
• Boundary Representation:
• Based on their external characteristics(its boundary)
• Shape characteristics .Such as corners & inflection.
• Regional Representation:
• Based on their internal characteristics(its region)
• Regional properties : color, texture .
COMPONENTS OF AN IMAGE PROCESSING
SYSTEM
• The basic components comprising a typical general – purpose system used for
digital image processing.
• Two elements are,
• Physical device that is sensitive to the energy radiated by the object we wish
to image.
• A device for converting the output of the physical sensing device into digital
form. Ex: digital video camera
COMPONENTS OF AN IMAGE PROCESSING SYSTEM
Fundamentals steps in Digital Image processing

Contenu connexe

Tendances

Homomorphic filtering
Homomorphic filteringHomomorphic filtering
Homomorphic filteringGautam Saxena
 
DIGITAL IMAGE PROCESSING - LECTURE NOTES
DIGITAL IMAGE PROCESSING - LECTURE NOTESDIGITAL IMAGE PROCESSING - LECTURE NOTES
DIGITAL IMAGE PROCESSING - LECTURE NOTESEzhilya venkat
 
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 ProcessingAmna
 
Image segmentation ppt
Image segmentation pptImage segmentation ppt
Image segmentation pptGichelle Amon
 
Image Processing Basics
Image Processing BasicsImage Processing Basics
Image Processing BasicsA B Shinde
 
Introduction to Image Compression
Introduction to Image CompressionIntroduction to Image Compression
Introduction to Image CompressionKalyan Acharjya
 
Digital Image Processing: Digital Image Fundamentals
Digital Image Processing: Digital Image FundamentalsDigital Image Processing: Digital Image Fundamentals
Digital Image Processing: Digital Image FundamentalsMostafa G. M. Mostafa
 
COM2304: Digital Image Fundamentals - I
COM2304: Digital Image Fundamentals - I COM2304: Digital Image Fundamentals - I
COM2304: Digital Image Fundamentals - I Hemantha Kulathilake
 
Digital Image Processing: Image Segmentation
Digital Image Processing: Image SegmentationDigital Image Processing: Image Segmentation
Digital Image Processing: Image SegmentationMostafa G. M. Mostafa
 
Fundamentals and image compression models
Fundamentals and image compression modelsFundamentals and image compression models
Fundamentals and image compression modelslavanya marichamy
 
Image Smoothing using Frequency Domain Filters
Image Smoothing using Frequency Domain FiltersImage Smoothing using Frequency Domain Filters
Image Smoothing using Frequency Domain FiltersSuhaila Afzana
 
5. gray level transformation
5. gray level transformation5. gray level transformation
5. gray level transformationMdFazleRabbi18
 
Frequency Domain Image Enhancement Techniques
Frequency Domain Image Enhancement TechniquesFrequency Domain Image Enhancement Techniques
Frequency Domain Image Enhancement TechniquesDiwaker Pant
 
Image enhancement techniques
Image enhancement techniquesImage enhancement techniques
Image enhancement techniquesBulbul Agrawal
 
Lecture 15 DCT, Walsh and Hadamard Transform
Lecture 15 DCT, Walsh and Hadamard TransformLecture 15 DCT, Walsh and Hadamard Transform
Lecture 15 DCT, Walsh and Hadamard TransformVARUN KUMAR
 
SPATIAL FILTERING IN IMAGE PROCESSING
SPATIAL FILTERING IN IMAGE PROCESSINGSPATIAL FILTERING IN IMAGE PROCESSING
SPATIAL FILTERING IN IMAGE PROCESSINGmuthu181188
 

Tendances (20)

image compression ppt
image compression pptimage compression ppt
image compression ppt
 
Homomorphic filtering
Homomorphic filteringHomomorphic filtering
Homomorphic filtering
 
Region based segmentation
Region based segmentationRegion based segmentation
Region based segmentation
 
DIGITAL IMAGE PROCESSING - LECTURE NOTES
DIGITAL IMAGE PROCESSING - LECTURE NOTESDIGITAL IMAGE PROCESSING - LECTURE NOTES
DIGITAL IMAGE PROCESSING - LECTURE NOTES
 
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
 
Image segmentation ppt
Image segmentation pptImage segmentation ppt
Image segmentation ppt
 
Image Processing Basics
Image Processing BasicsImage Processing Basics
Image Processing Basics
 
Sharpening spatial filters
Sharpening spatial filtersSharpening spatial filters
Sharpening spatial filters
 
Introduction to Image Compression
Introduction to Image CompressionIntroduction to Image Compression
Introduction to Image Compression
 
Digital Image Processing: Digital Image Fundamentals
Digital Image Processing: Digital Image FundamentalsDigital Image Processing: Digital Image Fundamentals
Digital Image Processing: Digital Image Fundamentals
 
COM2304: Digital Image Fundamentals - I
COM2304: Digital Image Fundamentals - I COM2304: Digital Image Fundamentals - I
COM2304: Digital Image Fundamentals - I
 
Digital Image Processing: Image Segmentation
Digital Image Processing: Image SegmentationDigital Image Processing: Image Segmentation
Digital Image Processing: Image Segmentation
 
Data Redundacy
Data RedundacyData Redundacy
Data Redundacy
 
Fundamentals and image compression models
Fundamentals and image compression modelsFundamentals and image compression models
Fundamentals and image compression models
 
Image Smoothing using Frequency Domain Filters
Image Smoothing using Frequency Domain FiltersImage Smoothing using Frequency Domain Filters
Image Smoothing using Frequency Domain Filters
 
5. gray level transformation
5. gray level transformation5. gray level transformation
5. gray level transformation
 
Frequency Domain Image Enhancement Techniques
Frequency Domain Image Enhancement TechniquesFrequency Domain Image Enhancement Techniques
Frequency Domain Image Enhancement Techniques
 
Image enhancement techniques
Image enhancement techniquesImage enhancement techniques
Image enhancement techniques
 
Lecture 15 DCT, Walsh and Hadamard Transform
Lecture 15 DCT, Walsh and Hadamard TransformLecture 15 DCT, Walsh and Hadamard Transform
Lecture 15 DCT, Walsh and Hadamard Transform
 
SPATIAL FILTERING IN IMAGE PROCESSING
SPATIAL FILTERING IN IMAGE PROCESSINGSPATIAL FILTERING IN IMAGE PROCESSING
SPATIAL FILTERING IN IMAGE PROCESSING
 

Similaire à Fundamentals steps in Digital Image processing

Extraction of region of interest in an image
Extraction of region of interest in an imageExtraction of region of interest in an image
Extraction of region of interest in an imageHarsukh Chandak
 
Image processing and compression.pptx
Image processing and compression.pptxImage processing and compression.pptx
Image processing and compression.pptxdudoo1
 
Digital image processing & computer graphics
Digital image processing & computer graphicsDigital image processing & computer graphics
Digital image processing & computer graphicsAnkit Garg
 
BEC007 -Digital image processing.pdf
BEC007  -Digital image processing.pdfBEC007  -Digital image processing.pdf
BEC007 -Digital image processing.pdfgopikahari7
 
2.FUNDAMENTALS OF DIGITAL IMAGE PROCESSING.pptx
2.FUNDAMENTALS OF DIGITAL IMAGE PROCESSING.pptx2.FUNDAMENTALS OF DIGITAL IMAGE PROCESSING.pptx
2.FUNDAMENTALS OF DIGITAL IMAGE PROCESSING.pptxVikashiniG
 
Computer Graphics Unit 5 notes for Manonmanium Sundaranar University
Computer Graphics  Unit 5 notes for Manonmanium Sundaranar UniversityComputer Graphics  Unit 5 notes for Manonmanium Sundaranar University
Computer Graphics Unit 5 notes for Manonmanium Sundaranar UniversityRajeswariR45
 
Image restoration and enhancement #2
Image restoration and enhancement #2 Image restoration and enhancement #2
Image restoration and enhancement #2 Gera Paulos
 
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 1himanshu swarnkar
 
Digital Image Processing
Digital Image ProcessingDigital Image Processing
Digital Image ProcessingReshma KC
 
Content-Based Image Retrieval Case Study
Content-Based Image Retrieval Case StudyContent-Based Image Retrieval Case Study
Content-Based Image Retrieval Case StudyLisa Kennedy
 
Dip lect2-Machine Vision Fundamentals
Dip  lect2-Machine Vision Fundamentals Dip  lect2-Machine Vision Fundamentals
Dip lect2-Machine Vision Fundamentals Abdul Abbasi
 
Digital_image_processing_-Vijaya_Raghavan.pdf
Digital_image_processing_-Vijaya_Raghavan.pdfDigital_image_processing_-Vijaya_Raghavan.pdf
Digital_image_processing_-Vijaya_Raghavan.pdfVaideshSiva1
 

Similaire à Fundamentals steps in Digital Image processing (20)

Extraction of region of interest in an image
Extraction of region of interest in an imageExtraction of region of interest in an image
Extraction of region of interest in an image
 
Image processing and compression.pptx
Image processing and compression.pptxImage processing and compression.pptx
Image processing and compression.pptx
 
Image processing.pdf
Image processing.pdfImage processing.pdf
Image processing.pdf
 
Digital image processing & computer graphics
Digital image processing & computer graphicsDigital image processing & computer graphics
Digital image processing & computer graphics
 
BEC007 -Digital image processing.pdf
BEC007  -Digital image processing.pdfBEC007  -Digital image processing.pdf
BEC007 -Digital image processing.pdf
 
DIP
DIPDIP
DIP
 
Digital image processing
Digital image processingDigital image processing
Digital image processing
 
2.FUNDAMENTALS OF DIGITAL IMAGE PROCESSING.pptx
2.FUNDAMENTALS OF DIGITAL IMAGE PROCESSING.pptx2.FUNDAMENTALS OF DIGITAL IMAGE PROCESSING.pptx
2.FUNDAMENTALS OF DIGITAL IMAGE PROCESSING.pptx
 
Computer Graphics Unit 5 notes for Manonmanium Sundaranar University
Computer Graphics  Unit 5 notes for Manonmanium Sundaranar UniversityComputer Graphics  Unit 5 notes for Manonmanium Sundaranar University
Computer Graphics Unit 5 notes for Manonmanium Sundaranar University
 
Dip
DipDip
Dip
 
Image processing
Image processingImage processing
Image processing
 
Image Processing.pdf
Image Processing.pdfImage Processing.pdf
Image Processing.pdf
 
Image restoration and enhancement #2
Image restoration and enhancement #2 Image restoration and enhancement #2
Image restoration and enhancement #2
 
Image processing
Image processing Image processing
Image processing
 
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
 
ACMP340.pptx
ACMP340.pptxACMP340.pptx
ACMP340.pptx
 
Digital Image Processing
Digital Image ProcessingDigital Image Processing
Digital Image Processing
 
Content-Based Image Retrieval Case Study
Content-Based Image Retrieval Case StudyContent-Based Image Retrieval Case Study
Content-Based Image Retrieval Case Study
 
Dip lect2-Machine Vision Fundamentals
Dip  lect2-Machine Vision Fundamentals Dip  lect2-Machine Vision Fundamentals
Dip lect2-Machine Vision Fundamentals
 
Digital_image_processing_-Vijaya_Raghavan.pdf
Digital_image_processing_-Vijaya_Raghavan.pdfDigital_image_processing_-Vijaya_Raghavan.pdf
Digital_image_processing_-Vijaya_Raghavan.pdf
 

Plus de KarthicaMarasamy

Plus de KarthicaMarasamy (13)

Roles of Datascience.pptx
Roles of Datascience.pptxRoles of Datascience.pptx
Roles of Datascience.pptx
 
DATASCIENCE.pptx
DATASCIENCE.pptxDATASCIENCE.pptx
DATASCIENCE.pptx
 
Software Testing 1.pptx
Software Testing 1.pptxSoftware Testing 1.pptx
Software Testing 1.pptx
 
powerpoint 1.pdf
powerpoint 1.pdfpowerpoint 1.pdf
powerpoint 1.pdf
 
class 3.pptx
class 3.pptxclass 3.pptx
class 3.pptx
 
class 2.pptx
class 2.pptxclass 2.pptx
class 2.pptx
 
Software Testing
Software TestingSoftware Testing
Software Testing
 
Network (Hub,switches)
Network  (Hub,switches)Network  (Hub,switches)
Network (Hub,switches)
 
Computer network layers
Computer network layersComputer network layers
Computer network layers
 
Presentation more c_programmingcharacter_and_string_handling_
Presentation more c_programmingcharacter_and_string_handling_Presentation more c_programmingcharacter_and_string_handling_
Presentation more c_programmingcharacter_and_string_handling_
 
C programming
C programmingC programming
C programming
 
DIGITAL IMAGE PROCESSING
DIGITAL IMAGE PROCESSINGDIGITAL IMAGE PROCESSING
DIGITAL IMAGE PROCESSING
 
Network
NetworkNetwork
Network
 

Dernier

psychiatric nursing HISTORY COLLECTION .docx
psychiatric  nursing HISTORY  COLLECTION  .docxpsychiatric  nursing HISTORY  COLLECTION  .docx
psychiatric nursing HISTORY COLLECTION .docxPoojaSen20
 
Holdier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfHoldier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfagholdier
 
An Overview of Mutual Funds Bcom Project.pdf
An Overview of Mutual Funds Bcom Project.pdfAn Overview of Mutual Funds Bcom Project.pdf
An Overview of Mutual Funds Bcom Project.pdfSanaAli374401
 
Grant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy ConsultingGrant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy ConsultingTechSoup
 
Ecological Succession. ( ECOSYSTEM, B. Pharmacy, 1st Year, Sem-II, Environmen...
Ecological Succession. ( ECOSYSTEM, B. Pharmacy, 1st Year, Sem-II, Environmen...Ecological Succession. ( ECOSYSTEM, B. Pharmacy, 1st Year, Sem-II, Environmen...
Ecological Succession. ( ECOSYSTEM, B. Pharmacy, 1st Year, Sem-II, Environmen...Shubhangi Sonawane
 
Basic Civil Engineering first year Notes- Chapter 4 Building.pptx
Basic Civil Engineering first year Notes- Chapter 4 Building.pptxBasic Civil Engineering first year Notes- Chapter 4 Building.pptx
Basic Civil Engineering first year Notes- Chapter 4 Building.pptxDenish Jangid
 
1029-Danh muc Sach Giao Khoa khoi 6.pdf
1029-Danh muc Sach Giao Khoa khoi  6.pdf1029-Danh muc Sach Giao Khoa khoi  6.pdf
1029-Danh muc Sach Giao Khoa khoi 6.pdfQucHHunhnh
 
microwave assisted reaction. General introduction
microwave assisted reaction. General introductionmicrowave assisted reaction. General introduction
microwave assisted reaction. General introductionMaksud Ahmed
 
Key note speaker Neum_Admir Softic_ENG.pdf
Key note speaker Neum_Admir Softic_ENG.pdfKey note speaker Neum_Admir Softic_ENG.pdf
Key note speaker Neum_Admir Softic_ENG.pdfAdmir Softic
 
Gardella_PRCampaignConclusion Pitch Letter
Gardella_PRCampaignConclusion Pitch LetterGardella_PRCampaignConclusion Pitch Letter
Gardella_PRCampaignConclusion Pitch LetterMateoGardella
 
Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17Celine George
 
APM Welcome, APM North West Network Conference, Synergies Across Sectors
APM Welcome, APM North West Network Conference, Synergies Across SectorsAPM Welcome, APM North West Network Conference, Synergies Across Sectors
APM Welcome, APM North West Network Conference, Synergies Across SectorsAssociation for Project Management
 
Application orientated numerical on hev.ppt
Application orientated numerical on hev.pptApplication orientated numerical on hev.ppt
Application orientated numerical on hev.pptRamjanShidvankar
 
Paris 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityParis 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityGeoBlogs
 
This PowerPoint helps students to consider the concept of infinity.
This PowerPoint helps students to consider the concept of infinity.This PowerPoint helps students to consider the concept of infinity.
This PowerPoint helps students to consider the concept of infinity.christianmathematics
 
Class 11th Physics NEET formula sheet pdf
Class 11th Physics NEET formula sheet pdfClass 11th Physics NEET formula sheet pdf
Class 11th Physics NEET formula sheet pdfAyushMahapatra5
 
Nutritional Needs Presentation - HLTH 104
Nutritional Needs Presentation - HLTH 104Nutritional Needs Presentation - HLTH 104
Nutritional Needs Presentation - HLTH 104misteraugie
 
Introduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsIntroduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsTechSoup
 
Mixin Classes in Odoo 17 How to Extend Models Using Mixin Classes
Mixin Classes in Odoo 17  How to Extend Models Using Mixin ClassesMixin Classes in Odoo 17  How to Extend Models Using Mixin Classes
Mixin Classes in Odoo 17 How to Extend Models Using Mixin ClassesCeline George
 

Dernier (20)

psychiatric nursing HISTORY COLLECTION .docx
psychiatric  nursing HISTORY  COLLECTION  .docxpsychiatric  nursing HISTORY  COLLECTION  .docx
psychiatric nursing HISTORY COLLECTION .docx
 
Holdier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfHoldier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdf
 
An Overview of Mutual Funds Bcom Project.pdf
An Overview of Mutual Funds Bcom Project.pdfAn Overview of Mutual Funds Bcom Project.pdf
An Overview of Mutual Funds Bcom Project.pdf
 
Grant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy ConsultingGrant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy Consulting
 
Ecological Succession. ( ECOSYSTEM, B. Pharmacy, 1st Year, Sem-II, Environmen...
Ecological Succession. ( ECOSYSTEM, B. Pharmacy, 1st Year, Sem-II, Environmen...Ecological Succession. ( ECOSYSTEM, B. Pharmacy, 1st Year, Sem-II, Environmen...
Ecological Succession. ( ECOSYSTEM, B. Pharmacy, 1st Year, Sem-II, Environmen...
 
Mehran University Newsletter Vol-X, Issue-I, 2024
Mehran University Newsletter Vol-X, Issue-I, 2024Mehran University Newsletter Vol-X, Issue-I, 2024
Mehran University Newsletter Vol-X, Issue-I, 2024
 
Basic Civil Engineering first year Notes- Chapter 4 Building.pptx
Basic Civil Engineering first year Notes- Chapter 4 Building.pptxBasic Civil Engineering first year Notes- Chapter 4 Building.pptx
Basic Civil Engineering first year Notes- Chapter 4 Building.pptx
 
1029-Danh muc Sach Giao Khoa khoi 6.pdf
1029-Danh muc Sach Giao Khoa khoi  6.pdf1029-Danh muc Sach Giao Khoa khoi  6.pdf
1029-Danh muc Sach Giao Khoa khoi 6.pdf
 
microwave assisted reaction. General introduction
microwave assisted reaction. General introductionmicrowave assisted reaction. General introduction
microwave assisted reaction. General introduction
 
Key note speaker Neum_Admir Softic_ENG.pdf
Key note speaker Neum_Admir Softic_ENG.pdfKey note speaker Neum_Admir Softic_ENG.pdf
Key note speaker Neum_Admir Softic_ENG.pdf
 
Gardella_PRCampaignConclusion Pitch Letter
Gardella_PRCampaignConclusion Pitch LetterGardella_PRCampaignConclusion Pitch Letter
Gardella_PRCampaignConclusion Pitch Letter
 
Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17
 
APM Welcome, APM North West Network Conference, Synergies Across Sectors
APM Welcome, APM North West Network Conference, Synergies Across SectorsAPM Welcome, APM North West Network Conference, Synergies Across Sectors
APM Welcome, APM North West Network Conference, Synergies Across Sectors
 
Application orientated numerical on hev.ppt
Application orientated numerical on hev.pptApplication orientated numerical on hev.ppt
Application orientated numerical on hev.ppt
 
Paris 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityParis 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activity
 
This PowerPoint helps students to consider the concept of infinity.
This PowerPoint helps students to consider the concept of infinity.This PowerPoint helps students to consider the concept of infinity.
This PowerPoint helps students to consider the concept of infinity.
 
Class 11th Physics NEET formula sheet pdf
Class 11th Physics NEET formula sheet pdfClass 11th Physics NEET formula sheet pdf
Class 11th Physics NEET formula sheet pdf
 
Nutritional Needs Presentation - HLTH 104
Nutritional Needs Presentation - HLTH 104Nutritional Needs Presentation - HLTH 104
Nutritional Needs Presentation - HLTH 104
 
Introduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsIntroduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The Basics
 
Mixin Classes in Odoo 17 How to Extend Models Using Mixin Classes
Mixin Classes in Odoo 17  How to Extend Models Using Mixin ClassesMixin Classes in Odoo 17  How to Extend Models Using Mixin Classes
Mixin Classes in Odoo 17 How to Extend Models Using Mixin Classes
 

Fundamentals steps in Digital Image processing

  • 1. CLASS -2 FUNDAMENTAL STEPS IN DIGITAL IMAGE PROCESSING • There is no general “theory” of image enhancement .When an image is processed for visual interpretation. • Enhancement techniques are so varied and use so many different image processing approaches. • Difficult to assemble a meaningful body of techniques suitable for enhancement in one chapter without extensive background development. • Beginners in the field of image processing generally find enhancement applications visually appealing , interesting and relatively simple to understand.
  • 2.
  • 3. IMAGE ACQUISITION • It is defined as the action of retrieving an image from some source, usually a hardware source of processing. • The image that is required is completely unprocessed.
  • 4. IMAGE ENHANCEMENT • It is widely used in computer graphics. • The objectives of image enhancement techniques is to process an image so that the result is more suitable than the original image for a specific application.
  • 6. COLOR IMAGE PROCESSING • It is an area that has been gaining in importance because of the significant increase in the use of digital images over the internet. • Color is used also in later chapter as the basics for extracting features of interest in an image.
  • 7.
  • 8. WAVELETS AND MULTIRESOLUTION PROCESSING • It is foundation for representing images in various degrees of resolution. • In data compression & for pyramidal representation in which images are subdivided successively into smaller regions.
  • 9.
  • 10.
  • 11.
  • 12. IMAGE REPRESENTATION & DESCRIPTION • After the image is segmented into regions, the resulting aggregate of segmented pixels is represented & described for further computer processing. • Representation in two ways : • Boundary Representation: • Based on their external characteristics(its boundary) • Shape characteristics .Such as corners & inflection. • Regional Representation: • Based on their internal characteristics(its region) • Regional properties : color, texture .
  • 13.
  • 14.
  • 15. COMPONENTS OF AN IMAGE PROCESSING SYSTEM • The basic components comprising a typical general – purpose system used for digital image processing. • Two elements are, • Physical device that is sensitive to the energy radiated by the object we wish to image. • A device for converting the output of the physical sensing device into digital form. Ex: digital video camera
  • 16. COMPONENTS OF AN IMAGE PROCESSING SYSTEM