SlideShare une entreprise Scribd logo
1  sur  1
Télécharger pour lire hors ligne
Computer Graphics (Assignment)
By: FarwaAbdul Hannan (12 – CS – 13)
Raster Images:
Raster images are those images that are made up of many small cells. These cells are known
as Pixels. A raster is stored in a computer as an array of numerical values. Each numerical value
represent the value of the pixel stored there. This array as a whole often known as Pixel Map.
Raster images are of two forms
1. Gray Scale Raster Images
2. Colored Raster Images
Gray Scale Raster Images:
These images as cleared from the name are in different shades of gray. The gray levels
range from black to white. As we know that raster images are stored in numerical values so if in
gray scale raster images, there are only two values of pixel then we call this image a bi-level image
as its pixel map can be consisted of an array of 1s or 0s or any two values from the one stored
between them (1s for black and 0s for white and the values between them represent different shades
of gray). A bi-level image is often known as 1 bit per pixel image. In a gray scale image if the
pixels take on more than two values then each pixel requires more than a single bit in memory and
their values are:
1. 2 bits/pixel produce 4 gray levels
2. 4 bits/pixel produce 16 gray levels
3. 8 bits/pixel produce 256 gray levels
Color Raster Images:
As the colored images represents our daily experience more closely as compared to gray
scale images so these images are more desirable. Color raster Images are most commonly used
images. Ina color raster image each pixel has a color value represented by a numerical value against
each color. In these images the colors are described as a combination of amounts of red, green and
blue colors. Each pixel value consist of 3-tuple like (red, green and blue) and these tuples
represents the intensities of red, green and blue colors respectively. The number of bits are used to
represent each pixel. Each value in the 3-tuple (red, green and blue) has a certain bit for it. For
example in the pixel values (0, 1, 1) 0 means off and 1 means on so here against the 3-tuple (red,
green, blue) red is off as it is 0 and green and blue are on as their pixel value in 1. Possible
combinations of colors with different pixel values are:
The colors other than these are produced by using different intensities of these colors.

Contenu connexe

En vedette

Linear combination of vector
Linear combination of vectorLinear combination of vector
Linear combination of vectorFarwa Ansari
 
Javadocx j option pane
Javadocx j option paneJavadocx j option pane
Javadocx j option paneFarwa Ansari
 
Digital logic and design's Lab 3
Digital logic and design's Lab 3Digital logic and design's Lab 3
Digital logic and design's Lab 3Farwa Ansari
 
Applications of Image Processing
Applications of Image ProcessingApplications of Image Processing
Applications of Image ProcessingFarwa Ansari
 
Manual of JAVA (more than Half)
Manual of JAVA (more than Half)Manual of JAVA (more than Half)
Manual of JAVA (more than Half)Farwa Ansari
 
JAVA Manual remaining
JAVA Manual remainingJAVA Manual remaining
JAVA Manual remainingFarwa Ansari
 
Digital logic and design's Lab 4 nand
Digital logic and design's Lab 4 nandDigital logic and design's Lab 4 nand
Digital logic and design's Lab 4 nandFarwa Ansari
 
Prefix and suffix of open gl
Prefix and suffix of open glPrefix and suffix of open gl
Prefix and suffix of open glFarwa Ansari
 
Summary of Simultaneous Multithreading: Maximizing On-Chip Parallelism
Summary of Simultaneous Multithreading: Maximizing On-Chip ParallelismSummary of Simultaneous Multithreading: Maximizing On-Chip Parallelism
Summary of Simultaneous Multithreading: Maximizing On-Chip ParallelismFarwa Ansari
 
Cohen sutherland algorithm
Cohen sutherland algorithmCohen sutherland algorithm
Cohen sutherland algorithmFarwa Ansari
 
Tomasulo Algorithm
Tomasulo AlgorithmTomasulo Algorithm
Tomasulo AlgorithmFarwa Ansari
 
Chapter 4: Lexical & Syntax Analysis (Programming Exercises)
Chapter 4: Lexical & Syntax Analysis (Programming Exercises)Chapter 4: Lexical & Syntax Analysis (Programming Exercises)
Chapter 4: Lexical & Syntax Analysis (Programming Exercises)Farwa Ansari
 
Mission statement and Vision statement of 3 Different Companies
Mission statement and Vision statement of 3 Different CompaniesMission statement and Vision statement of 3 Different Companies
Mission statement and Vision statement of 3 Different CompaniesFarwa Ansari
 
Implementation & Challenges of IPv6
Implementation & Challenges of IPv6Implementation & Challenges of IPv6
Implementation & Challenges of IPv6 Farwa Ansari
 
IPv6 Implementation challenges
IPv6 Implementation challengesIPv6 Implementation challenges
IPv6 Implementation challengesFarwa Ansari
 
DLDLab 8 half adder
DLDLab 8 half adderDLDLab 8 half adder
DLDLab 8 half adderFarwa Ansari
 
Graphic display devices
Graphic display devicesGraphic display devices
Graphic display devicesFarwa Ansari
 
Memory Hierarchy Design, Basics, Cache Optimization, Address Translation
Memory Hierarchy Design, Basics, Cache Optimization, Address TranslationMemory Hierarchy Design, Basics, Cache Optimization, Address Translation
Memory Hierarchy Design, Basics, Cache Optimization, Address TranslationFarwa Ansari
 

En vedette (20)

Linear combination of vector
Linear combination of vectorLinear combination of vector
Linear combination of vector
 
Javadocx j option pane
Javadocx j option paneJavadocx j option pane
Javadocx j option pane
 
Digital logic and design's Lab 3
Digital logic and design's Lab 3Digital logic and design's Lab 3
Digital logic and design's Lab 3
 
Applications of Image Processing
Applications of Image ProcessingApplications of Image Processing
Applications of Image Processing
 
Scaling
ScalingScaling
Scaling
 
Manual of JAVA (more than Half)
Manual of JAVA (more than Half)Manual of JAVA (more than Half)
Manual of JAVA (more than Half)
 
JAVA Manual remaining
JAVA Manual remainingJAVA Manual remaining
JAVA Manual remaining
 
Digital logic and design's Lab 4 nand
Digital logic and design's Lab 4 nandDigital logic and design's Lab 4 nand
Digital logic and design's Lab 4 nand
 
Prefix and suffix of open gl
Prefix and suffix of open glPrefix and suffix of open gl
Prefix and suffix of open gl
 
Summary of Simultaneous Multithreading: Maximizing On-Chip Parallelism
Summary of Simultaneous Multithreading: Maximizing On-Chip ParallelismSummary of Simultaneous Multithreading: Maximizing On-Chip Parallelism
Summary of Simultaneous Multithreading: Maximizing On-Chip Parallelism
 
Cohen sutherland algorithm
Cohen sutherland algorithmCohen sutherland algorithm
Cohen sutherland algorithm
 
Templates
TemplatesTemplates
Templates
 
Tomasulo Algorithm
Tomasulo AlgorithmTomasulo Algorithm
Tomasulo Algorithm
 
Chapter 4: Lexical & Syntax Analysis (Programming Exercises)
Chapter 4: Lexical & Syntax Analysis (Programming Exercises)Chapter 4: Lexical & Syntax Analysis (Programming Exercises)
Chapter 4: Lexical & Syntax Analysis (Programming Exercises)
 
Mission statement and Vision statement of 3 Different Companies
Mission statement and Vision statement of 3 Different CompaniesMission statement and Vision statement of 3 Different Companies
Mission statement and Vision statement of 3 Different Companies
 
Implementation & Challenges of IPv6
Implementation & Challenges of IPv6Implementation & Challenges of IPv6
Implementation & Challenges of IPv6
 
IPv6 Implementation challenges
IPv6 Implementation challengesIPv6 Implementation challenges
IPv6 Implementation challenges
 
DLDLab 8 half adder
DLDLab 8 half adderDLDLab 8 half adder
DLDLab 8 half adder
 
Graphic display devices
Graphic display devicesGraphic display devices
Graphic display devices
 
Memory Hierarchy Design, Basics, Cache Optimization, Address Translation
Memory Hierarchy Design, Basics, Cache Optimization, Address TranslationMemory Hierarchy Design, Basics, Cache Optimization, Address Translation
Memory Hierarchy Design, Basics, Cache Optimization, Address Translation
 

Similaire à Raster images (assignment)

Lecture 2-2023.pdf
Lecture 2-2023.pdfLecture 2-2023.pdf
Lecture 2-2023.pdfssuserff72e4
 
Lecture 2-2023.pdf
Lecture 2-2023.pdfLecture 2-2023.pdf
Lecture 2-2023.pdfssuserff72e4
 
IJCER (www.ijceronline.com) International Journal of computational Engineerin...
IJCER (www.ijceronline.com) International Journal of computational Engineerin...IJCER (www.ijceronline.com) International Journal of computational Engineerin...
IJCER (www.ijceronline.com) International Journal of computational Engineerin...ijceronline
 
Sign Language Recognition Using Image Processing For Mute People
Sign Language Recognition Using Image Processing For Mute PeopleSign Language Recognition Using Image Processing For Mute People
Sign Language Recognition Using Image Processing For Mute Peoplepaperpublications3
 
Technical concepts for graphic design production 4
Technical concepts for graphic design production 4Technical concepts for graphic design production 4
Technical concepts for graphic design production 4Ahmed Ismail
 
Basics of image processing & analysis
Basics of image processing & analysisBasics of image processing & analysis
Basics of image processing & analysisMohsin Siddique
 
Colorization of Gray Scale Images in YCbCr Color Space Using Texture Extract...
Colorization of Gray Scale Images in YCbCr Color Space Using  Texture Extract...Colorization of Gray Scale Images in YCbCr Color Space Using  Texture Extract...
Colorization of Gray Scale Images in YCbCr Color Space Using Texture Extract...IOSR Journals
 
Multimedia graphics and image data representation
Multimedia graphics and image data representationMultimedia graphics and image data representation
Multimedia graphics and image data representationMazin Alwaaly
 
RGB Color Model and Monitor Resolution
RGB Color Model and Monitor ResolutionRGB Color Model and Monitor Resolution
RGB Color Model and Monitor ResolutionAdya Tiwari
 

Similaire à Raster images (assignment) (20)

About Color
About ColorAbout Color
About Color
 
Types of images
Types of imagesTypes of images
Types of images
 
Types of images
Types of imagesTypes of images
Types of images
 
Types of images
Types of imagesTypes of images
Types of images
 
Sec 2.pdf
Sec 2.pdfSec 2.pdf
Sec 2.pdf
 
Lecture 2-2023.pdf
Lecture 2-2023.pdfLecture 2-2023.pdf
Lecture 2-2023.pdf
 
Lecture 2-2023.pdf
Lecture 2-2023.pdfLecture 2-2023.pdf
Lecture 2-2023.pdf
 
IJCER (www.ijceronline.com) International Journal of computational Engineerin...
IJCER (www.ijceronline.com) International Journal of computational Engineerin...IJCER (www.ijceronline.com) International Journal of computational Engineerin...
IJCER (www.ijceronline.com) International Journal of computational Engineerin...
 
Image processing
Image processingImage processing
Image processing
 
Psuedo color
Psuedo colorPsuedo color
Psuedo color
 
Sign Language Recognition Using Image Processing For Mute People
Sign Language Recognition Using Image Processing For Mute PeopleSign Language Recognition Using Image Processing For Mute People
Sign Language Recognition Using Image Processing For Mute People
 
CLASS 1.1.pptx
CLASS 1.1.pptxCLASS 1.1.pptx
CLASS 1.1.pptx
 
Technical concepts for graphic design production 4
Technical concepts for graphic design production 4Technical concepts for graphic design production 4
Technical concepts for graphic design production 4
 
Color
ColorColor
Color
 
Basics of image processing & analysis
Basics of image processing & analysisBasics of image processing & analysis
Basics of image processing & analysis
 
Colorization of Gray Scale Images in YCbCr Color Space Using Texture Extract...
Colorization of Gray Scale Images in YCbCr Color Space Using  Texture Extract...Colorization of Gray Scale Images in YCbCr Color Space Using  Texture Extract...
Colorization of Gray Scale Images in YCbCr Color Space Using Texture Extract...
 
Multimedia graphics and image data representation
Multimedia graphics and image data representationMultimedia graphics and image data representation
Multimedia graphics and image data representation
 
Dip
DipDip
Dip
 
RGB Color Model and Monitor Resolution
RGB Color Model and Monitor ResolutionRGB Color Model and Monitor Resolution
RGB Color Model and Monitor Resolution
 
Bitmap vector2
Bitmap vector2Bitmap vector2
Bitmap vector2
 

Plus de Farwa Ansari

Energy Harvesting Techniques in Wireless Sensor Networks – A Survey
Energy Harvesting Techniques in Wireless Sensor Networks – A SurveyEnergy Harvesting Techniques in Wireless Sensor Networks – A Survey
Energy Harvesting Techniques in Wireless Sensor Networks – A SurveyFarwa Ansari
 
Micro-services architecture
Micro-services architectureMicro-services architecture
Micro-services architectureFarwa Ansari
 
Software Design Patterns - An Overview
Software Design Patterns - An OverviewSoftware Design Patterns - An Overview
Software Design Patterns - An OverviewFarwa Ansari
 
Optimizing the memory management of a virtual machine monitor on a NUMA syste...
Optimizing the memory management of a virtual machine monitor on a NUMA syste...Optimizing the memory management of a virtual machine monitor on a NUMA syste...
Optimizing the memory management of a virtual machine monitor on a NUMA syste...Farwa Ansari
 
Fault Tolerance Typed Assembly Language - A graphical overview
Fault Tolerance Typed Assembly Language - A graphical overviewFault Tolerance Typed Assembly Language - A graphical overview
Fault Tolerance Typed Assembly Language - A graphical overviewFarwa Ansari
 
Comparative Analysis of Face Recognition Methodologies and Techniques
Comparative Analysis of Face Recognition Methodologies and TechniquesComparative Analysis of Face Recognition Methodologies and Techniques
Comparative Analysis of Face Recognition Methodologies and TechniquesFarwa Ansari
 
Chapter 5: Names, Bindings and Scopes (review Questions and Problem Set)
Chapter 5: Names, Bindings and Scopes (review Questions and Problem Set)Chapter 5: Names, Bindings and Scopes (review Questions and Problem Set)
Chapter 5: Names, Bindings and Scopes (review Questions and Problem Set)Farwa Ansari
 
Business plan of a software house
Business plan of a software houseBusiness plan of a software house
Business plan of a software houseFarwa Ansari
 
Hacking and Hackers
Hacking and HackersHacking and Hackers
Hacking and HackersFarwa Ansari
 

Plus de Farwa Ansari (10)

Energy Harvesting Techniques in Wireless Sensor Networks – A Survey
Energy Harvesting Techniques in Wireless Sensor Networks – A SurveyEnergy Harvesting Techniques in Wireless Sensor Networks – A Survey
Energy Harvesting Techniques in Wireless Sensor Networks – A Survey
 
Micro-services architecture
Micro-services architectureMicro-services architecture
Micro-services architecture
 
Software Design Patterns - An Overview
Software Design Patterns - An OverviewSoftware Design Patterns - An Overview
Software Design Patterns - An Overview
 
Optimizing the memory management of a virtual machine monitor on a NUMA syste...
Optimizing the memory management of a virtual machine monitor on a NUMA syste...Optimizing the memory management of a virtual machine monitor on a NUMA syste...
Optimizing the memory management of a virtual machine monitor on a NUMA syste...
 
Fault Tolerance Typed Assembly Language - A graphical overview
Fault Tolerance Typed Assembly Language - A graphical overviewFault Tolerance Typed Assembly Language - A graphical overview
Fault Tolerance Typed Assembly Language - A graphical overview
 
Comparative Analysis of Face Recognition Methodologies and Techniques
Comparative Analysis of Face Recognition Methodologies and TechniquesComparative Analysis of Face Recognition Methodologies and Techniques
Comparative Analysis of Face Recognition Methodologies and Techniques
 
Chapter 5: Names, Bindings and Scopes (review Questions and Problem Set)
Chapter 5: Names, Bindings and Scopes (review Questions and Problem Set)Chapter 5: Names, Bindings and Scopes (review Questions and Problem Set)
Chapter 5: Names, Bindings and Scopes (review Questions and Problem Set)
 
Business plan of a software house
Business plan of a software houseBusiness plan of a software house
Business plan of a software house
 
Dld (lab 1 & 2)
Dld (lab 1 & 2)Dld (lab 1 & 2)
Dld (lab 1 & 2)
 
Hacking and Hackers
Hacking and HackersHacking and Hackers
Hacking and Hackers
 

Dernier

microwave assisted reaction. General introduction
microwave assisted reaction. General introductionmicrowave assisted reaction. General introduction
microwave assisted reaction. General introductionMaksud Ahmed
 
PROCESS RECORDING FORMAT.docx
PROCESS      RECORDING        FORMAT.docxPROCESS      RECORDING        FORMAT.docx
PROCESS RECORDING FORMAT.docxPoojaSen20
 
SECOND SEMESTER TOPIC COVERAGE SY 2023-2024 Trends, Networks, and Critical Th...
SECOND SEMESTER TOPIC COVERAGE SY 2023-2024 Trends, Networks, and Critical Th...SECOND SEMESTER TOPIC COVERAGE SY 2023-2024 Trends, Networks, and Critical Th...
SECOND SEMESTER TOPIC COVERAGE SY 2023-2024 Trends, Networks, and Critical Th...KokoStevan
 
The basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptxThe basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptxheathfieldcps1
 
ICT Role in 21st Century Education & its Challenges.pptx
ICT Role in 21st Century Education & its Challenges.pptxICT Role in 21st Century Education & its Challenges.pptx
ICT Role in 21st Century Education & its Challenges.pptxAreebaZafar22
 
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
 
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
 
How to Give a Domain for a Field in Odoo 17
How to Give a Domain for a Field in Odoo 17How to Give a Domain for a Field in Odoo 17
How to Give a Domain for a Field in Odoo 17Celine George
 
Unit-IV; Professional Sales Representative (PSR).pptx
Unit-IV; Professional Sales Representative (PSR).pptxUnit-IV; Professional Sales Representative (PSR).pptx
Unit-IV; Professional Sales Representative (PSR).pptxVishalSingh1417
 
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
 
Russian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in Delhi
Russian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in DelhiRussian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in Delhi
Russian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in Delhikauryashika82
 
Making and Justifying Mathematical Decisions.pdf
Making and Justifying Mathematical Decisions.pdfMaking and Justifying Mathematical Decisions.pdf
Making and Justifying Mathematical Decisions.pdfChris Hunter
 
Z Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot GraphZ Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot GraphThiyagu K
 
Introduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsIntroduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsTechSoup
 
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
 
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...EduSkills OECD
 
1029 - Danh muc Sach Giao Khoa 10 . pdf
1029 -  Danh muc Sach Giao Khoa 10 . pdf1029 -  Danh muc Sach Giao Khoa 10 . pdf
1029 - Danh muc Sach Giao Khoa 10 . pdfQucHHunhnh
 

Dernier (20)

microwave assisted reaction. General introduction
microwave assisted reaction. General introductionmicrowave assisted reaction. General introduction
microwave assisted reaction. General introduction
 
PROCESS RECORDING FORMAT.docx
PROCESS      RECORDING        FORMAT.docxPROCESS      RECORDING        FORMAT.docx
PROCESS RECORDING FORMAT.docx
 
SECOND SEMESTER TOPIC COVERAGE SY 2023-2024 Trends, Networks, and Critical Th...
SECOND SEMESTER TOPIC COVERAGE SY 2023-2024 Trends, Networks, and Critical Th...SECOND SEMESTER TOPIC COVERAGE SY 2023-2024 Trends, Networks, and Critical Th...
SECOND SEMESTER TOPIC COVERAGE SY 2023-2024 Trends, Networks, and Critical Th...
 
The basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptxThe basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptx
 
ICT Role in 21st Century Education & its Challenges.pptx
ICT Role in 21st Century Education & its Challenges.pptxICT Role in 21st Century Education & its Challenges.pptx
ICT Role in 21st Century Education & its Challenges.pptx
 
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
 
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...
 
How to Give a Domain for a Field in Odoo 17
How to Give a Domain for a Field in Odoo 17How to Give a Domain for a Field in Odoo 17
How to Give a Domain for a Field in Odoo 17
 
Unit-IV; Professional Sales Representative (PSR).pptx
Unit-IV; Professional Sales Representative (PSR).pptxUnit-IV; Professional Sales Representative (PSR).pptx
Unit-IV; Professional Sales Representative (PSR).pptx
 
Mattingly "AI & Prompt Design: Structured Data, Assistants, & RAG"
Mattingly "AI & Prompt Design: Structured Data, Assistants, & RAG"Mattingly "AI & Prompt Design: Structured Data, Assistants, & RAG"
Mattingly "AI & Prompt Design: Structured Data, Assistants, & RAG"
 
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
 
Código Creativo y Arte de Software | Unidad 1
Código Creativo y Arte de Software | Unidad 1Código Creativo y Arte de Software | Unidad 1
Código Creativo y Arte de Software | Unidad 1
 
Russian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in Delhi
Russian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in DelhiRussian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in Delhi
Russian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in Delhi
 
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
 
Making and Justifying Mathematical Decisions.pdf
Making and Justifying Mathematical Decisions.pdfMaking and Justifying Mathematical Decisions.pdf
Making and Justifying Mathematical Decisions.pdf
 
Z Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot GraphZ Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot Graph
 
Introduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsIntroduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The Basics
 
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
 
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
 
1029 - Danh muc Sach Giao Khoa 10 . pdf
1029 -  Danh muc Sach Giao Khoa 10 . pdf1029 -  Danh muc Sach Giao Khoa 10 . pdf
1029 - Danh muc Sach Giao Khoa 10 . pdf
 

Raster images (assignment)

  • 1. Computer Graphics (Assignment) By: FarwaAbdul Hannan (12 – CS – 13) Raster Images: Raster images are those images that are made up of many small cells. These cells are known as Pixels. A raster is stored in a computer as an array of numerical values. Each numerical value represent the value of the pixel stored there. This array as a whole often known as Pixel Map. Raster images are of two forms 1. Gray Scale Raster Images 2. Colored Raster Images Gray Scale Raster Images: These images as cleared from the name are in different shades of gray. The gray levels range from black to white. As we know that raster images are stored in numerical values so if in gray scale raster images, there are only two values of pixel then we call this image a bi-level image as its pixel map can be consisted of an array of 1s or 0s or any two values from the one stored between them (1s for black and 0s for white and the values between them represent different shades of gray). A bi-level image is often known as 1 bit per pixel image. In a gray scale image if the pixels take on more than two values then each pixel requires more than a single bit in memory and their values are: 1. 2 bits/pixel produce 4 gray levels 2. 4 bits/pixel produce 16 gray levels 3. 8 bits/pixel produce 256 gray levels Color Raster Images: As the colored images represents our daily experience more closely as compared to gray scale images so these images are more desirable. Color raster Images are most commonly used images. Ina color raster image each pixel has a color value represented by a numerical value against each color. In these images the colors are described as a combination of amounts of red, green and blue colors. Each pixel value consist of 3-tuple like (red, green and blue) and these tuples represents the intensities of red, green and blue colors respectively. The number of bits are used to represent each pixel. Each value in the 3-tuple (red, green and blue) has a certain bit for it. For example in the pixel values (0, 1, 1) 0 means off and 1 means on so here against the 3-tuple (red, green, blue) red is off as it is 0 and green and blue are on as their pixel value in 1. Possible combinations of colors with different pixel values are: The colors other than these are produced by using different intensities of these colors.