It is the basic introduction of how the images will be captured and converted form analog to digital format by using sampling and quantization process and further algorithms will be apply on the digitized image.
It is the basic introduction of how the images will be captured and converted form analog to digital format by using sampling and quantization process and further algorithms will be apply on the digitized image.
Fundamental steps in Digital Image ProcessingShubham Jain
Fundamental Steps in Digital Image Processing: Image acquisition, enhancement, restoration, etc. For written notes and pdf visit: https://buzztech.in/fundamental-steps-in-digital-image-processing
Why Image compression is important?
How Image compression has come a long way?
Image compression is nearly mature, but there is always room for improvement.
Introduction to Digital Image Processing Using MATLABRay Phan
This was a 3 hour presentation given to undergraduate and graduate students at Ryerson University in Toronto, Ontario, Canada on an introduction to Digital Image Processing using the MATLAB programming environment. This should provide the basics of performing the most common image processing tasks, as well as providing an introduction to how digital images work and how they're formed.
You can access the images and code that I created and used here: https://www.dropbox.com/sh/s7trtj4xngy3cpq/AAAoAK7Lf-aDRCDFOzYQW64ka?dl=0
The students can learn about basics of image processing using matlab.
It explains the image operations with the help of examples and Matlab codes.
Students can fine sample images and .m code from the link given in slides.
Technical concepts for graphic design production 4Ahmed Ismail
Technical concepts for graphic design production includes:
1- History Of Graphic Design.
2- Graphics Types.
3- Bitmaps.
4- Color Gamut.
5- Files Formats.
6- Resolutions.
7- Color Depth.
8- Document Structure.
9- Digital Printing.
10 - pdf.
11- Color Management System CMS.
Design of Image Compression Algorithm using MATLABIJEEE
This paper gives the idea of recent developments in the field of image security and improvements in image security. Images are used in many applications and to provide
image security using image encryption and authentication.
Image encryption techniques scramble the pixels of the image and decrease the correlation among the pixels, such that the encrypted image cannot be accessed by unauthorized user.
Establishment of an Efficient Color Model from Existing Models for Better Gam...CSCJournals
Human vision is an important factor in the areas of image processing. Research has been done for years to make automatic image processing but still human intervention can not be denied and thus better human intervention is necessary. Two most important points are required to improve human vision which are light and color. Gamma encoder is the one which helps to improve the properties of human vision and thus to maintain visual quality gamma encoding is necessary.
It is to mention that all through the computer graphics RGB (Red, Green, and Blue) color space is vastly used. Moreover, for computer graphics RGB color space is called the most established choice to acquire desired color. RGB color space has a great effort on simplifying the design and architecture of a system. However, RGB struggles to deal efficiently for the images those belong to the real-world.
Images are captured using cameras, videos and other devices using different magnifications. In most cases during processing, in compare to the original outlook the images appear either dark or bright in contrast. Human vision affects and thus poor quality image analysis may occur. Consequently this poor manual image analysis may have huge difference from the computational image analysis outcome. Question may arise here why we will use gamma encoding when histogram equalization or histogram normalization can enhance images. Enhancing images does not improve human visualization quality all the time because sometimes it brightens the image quality when it is needed to darken and vice-versa. Human vision reflects under universal illumination environment (not pitch black or blindingly bright) thus follows an approximate gamma or power function. Hence, this is not a good idea to brighten images all the time when better human visualization can be obtained while darkening the images. Better human visualization is important for manual image processing which leads to compare the outcome with the semiautomated or automated one. Considering the importance of gamma encoding in image processing we propose an efficient color model which will help to improve visual quality for manual processing as well as will lead analyzers to analyze images automatically for comparison and testing purpose.
This is the basic introductory presentation for beginners. It gives you the idea about what is image processing means. The presentation consists of introduction to digital image processing, image enhancement, image filtering, finding an image edge, image analysis, tools for image processing and finally some application of digital image processing.
a collection of terminologies used in the game development industry, from my point of view any one who intends to work in that business should understand them.
Initial Introduction of Image processing is included in these slides which contain 1. Introduction of Image Processing
2.Elements of visual perception
3. Image sensing and Quantization
4.A simple image formation model
5.Basic concept of Sampling and Quantization
Reader will find it easy to understand the topics described here in slides . A detailed description of each topic illustrated here.
Please read and if you like do comments also.... Thanks
Photo and Graphic editing tools for bloggersSarah Arrow
As a blogger (or anyone with an online business for that matter) you'll need to edit and manipulate graphics, images and photos. Here are 10 tools that will help you.
Fundamental steps in Digital Image ProcessingShubham Jain
Fundamental Steps in Digital Image Processing: Image acquisition, enhancement, restoration, etc. For written notes and pdf visit: https://buzztech.in/fundamental-steps-in-digital-image-processing
Why Image compression is important?
How Image compression has come a long way?
Image compression is nearly mature, but there is always room for improvement.
Introduction to Digital Image Processing Using MATLABRay Phan
This was a 3 hour presentation given to undergraduate and graduate students at Ryerson University in Toronto, Ontario, Canada on an introduction to Digital Image Processing using the MATLAB programming environment. This should provide the basics of performing the most common image processing tasks, as well as providing an introduction to how digital images work and how they're formed.
You can access the images and code that I created and used here: https://www.dropbox.com/sh/s7trtj4xngy3cpq/AAAoAK7Lf-aDRCDFOzYQW64ka?dl=0
The students can learn about basics of image processing using matlab.
It explains the image operations with the help of examples and Matlab codes.
Students can fine sample images and .m code from the link given in slides.
Technical concepts for graphic design production 4Ahmed Ismail
Technical concepts for graphic design production includes:
1- History Of Graphic Design.
2- Graphics Types.
3- Bitmaps.
4- Color Gamut.
5- Files Formats.
6- Resolutions.
7- Color Depth.
8- Document Structure.
9- Digital Printing.
10 - pdf.
11- Color Management System CMS.
Design of Image Compression Algorithm using MATLABIJEEE
This paper gives the idea of recent developments in the field of image security and improvements in image security. Images are used in many applications and to provide
image security using image encryption and authentication.
Image encryption techniques scramble the pixels of the image and decrease the correlation among the pixels, such that the encrypted image cannot be accessed by unauthorized user.
Establishment of an Efficient Color Model from Existing Models for Better Gam...CSCJournals
Human vision is an important factor in the areas of image processing. Research has been done for years to make automatic image processing but still human intervention can not be denied and thus better human intervention is necessary. Two most important points are required to improve human vision which are light and color. Gamma encoder is the one which helps to improve the properties of human vision and thus to maintain visual quality gamma encoding is necessary.
It is to mention that all through the computer graphics RGB (Red, Green, and Blue) color space is vastly used. Moreover, for computer graphics RGB color space is called the most established choice to acquire desired color. RGB color space has a great effort on simplifying the design and architecture of a system. However, RGB struggles to deal efficiently for the images those belong to the real-world.
Images are captured using cameras, videos and other devices using different magnifications. In most cases during processing, in compare to the original outlook the images appear either dark or bright in contrast. Human vision affects and thus poor quality image analysis may occur. Consequently this poor manual image analysis may have huge difference from the computational image analysis outcome. Question may arise here why we will use gamma encoding when histogram equalization or histogram normalization can enhance images. Enhancing images does not improve human visualization quality all the time because sometimes it brightens the image quality when it is needed to darken and vice-versa. Human vision reflects under universal illumination environment (not pitch black or blindingly bright) thus follows an approximate gamma or power function. Hence, this is not a good idea to brighten images all the time when better human visualization can be obtained while darkening the images. Better human visualization is important for manual image processing which leads to compare the outcome with the semiautomated or automated one. Considering the importance of gamma encoding in image processing we propose an efficient color model which will help to improve visual quality for manual processing as well as will lead analyzers to analyze images automatically for comparison and testing purpose.
This is the basic introductory presentation for beginners. It gives you the idea about what is image processing means. The presentation consists of introduction to digital image processing, image enhancement, image filtering, finding an image edge, image analysis, tools for image processing and finally some application of digital image processing.
a collection of terminologies used in the game development industry, from my point of view any one who intends to work in that business should understand them.
Initial Introduction of Image processing is included in these slides which contain 1. Introduction of Image Processing
2.Elements of visual perception
3. Image sensing and Quantization
4.A simple image formation model
5.Basic concept of Sampling and Quantization
Reader will find it easy to understand the topics described here in slides . A detailed description of each topic illustrated here.
Please read and if you like do comments also.... Thanks
Photo and Graphic editing tools for bloggersSarah Arrow
As a blogger (or anyone with an online business for that matter) you'll need to edit and manipulate graphics, images and photos. Here are 10 tools that will help you.
Here's a quick guide on how to make a hyperlink in HTML code from Marketing Support Alliance. For more tips and tricks please visit www.marketingsupportalliance.com
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A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
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Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
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Image graphics-introduction
1. Study guide for week 3:
Topic 1 – graphic/image editing
KUM7088 Multimedia in Music Education
Composed by
Gerhard Lock
2. KUM7088 Multimedia in Music Education
Composed by Gerhard Lock
Topic 1 – graphics/image
The student knows and is able to apply within a proper meaningful context simple graphic
and image composition principles and has the skill to cut/reduce image files into web-
formats.
At least 3 graphics/images with different content/aim are to be done.
1. Graphics
1.1 Raster graphics vs vector graphics
2. Image
2.1 Making pictures
2.2 Technical parameters/color codes and digital representation of pictures
3. 1. Graphics
1.1 Raster graphics vs vector graphics
Raster graphics and vector graphics, application and preference cases*
Both graphic types, raster and vector graphics, have preferred application cases. As basic material
of a design/layout one should always prefer vector graphics, because the result is better in
quality.
The example above is first saved
as raster graphic and than
enlarged. The example below is
saved as vector graphic and
thanks to that the size can be
scaled fluently.
The most important difference
between the examples emerges
while looking at the diagonal and
curved lines, cogged edges turn
the quality of the first picture down,
the vector graphic edges of the
second picture are smooth.
* Aara Design Contor: http://www.aara.ee/Rastergraafika_ja_vektorgraafika_16.htm (translated by G. Lock)
4. 1. Graphics
1.1 Raster graphics vs vector graphics
Raster graphics and vector graphics, application and preference cases*
Most preferred raster graphics formats are .jpg, .gif and .png. The picture is saved with a defined
resolution enabling the optimized result.
The keyword here is optimizing which enables e.g. in the internet a smaller file size and therefore
a faster loading time. Keep in mind that a raster graphic is optimized for web view only and
doesn't befit for consecutive modifying and print layout purpose.
Vector graphics the objects are saved as vectors [lines joining dots] and they can be used for
further layout and modifying (enlarging or minimizing, color changing, detaching objects etc.)
Most popular vector graphics' formats are Adobe Illustraator (.ai) and CorelDRAW (.cdr). [But
also free software OpenOffice Draw offers well working solutions.] In that case giving the
layouter earlier created materials (logo or some template layout) you should always sent also
the basic vectore graphics file.
* Aara Design Contor: http://www.aara.ee/Rastergraafika_ja_vektorgraafika_16.htm (translated by G. Lock)
5. 2. Image
2.1 Making pictures
Making pictures take into account the following basic principles:
1) Composition
- position of people/animals/objects in respect to the whole picture
- central perspective, golden cut (see calculator http://goldenratiocalculator.com ) etc.
- color balance of people/animals/objects in respect to the whole picture
2) Lighting
- from which position the light source comes in respect to objects
- shades (of objects) and overlighting, making pictures against the sun (special effects)
- indoor vs outdoor; using flash (only if really needed)
3) Shutter speed and auto focus
- automatic cameras choose it itself, use predefined auto settings carefully
4) Resolution
- modern digital cameras offer several resolutions (according to which the file size/quality de-/increases)
5) Camera corner (position in respect to the object)
6) Zooming
- only professional cameras allow quality zooming, try to avoid zooming if possible
See Digital Photography Tutorials: http://www.cambridgeincolour.com/tutorials.htm,
http://lifehacker.com/5815742/basics-of-photography-the-complete-guide
6. 2. Image
2.2 Technical parameters/color codes and digital representation of pictures
Pixel • dot on a screen, print, etc.
To define digital pictures the element pixel (pel) is used, its a physical dot in a raster or the tiniest localizable
screen picture element. Position of pixels is connected with physical coordinates. LCD's (liquid crystal
display) work with 2-dimensional rasters and and use dots or squares, CRT (cathode ray tube) pixels are
connected with the defined emerging and disappearing time.
7. 2. Image
2.2 Technical parameters/color codes and digital representation of pictures
Megapixel • MP, Mpx
It equalizes 1 million pixels, which is used not only concerning numbers of pixels in the picture, but also to
express the number of image sensor's elements of digital cameras or digital screens.
For example a camera, which takes pictures with resolution 2048 × 1536 pixel, uses normally some additional
rows and columns for the sensor's elements and seda is called 3.2 or 3.4 megapixel according to the
“efective” or “total” number of pixels in opposition to the number of pixels of the final picture: 2048 × 1536 =
3,145,72
PPI = pixel per inch
PPI or pixel density is a parameter of resolution: typical in computer screens, picture scanners, digital camera
sensors; its the tiniest controllable on screen represented element.
1 inch = 2.54 centimeter
Kalkulaator: www.manuelsweb.com/in_cm.htm
8. 2. Image
2.2 Technical parameters/color codes and digital representation of pictures
RGB colors – additive model
8 bits, integer 0–255.
256*256*256=16777216 possible colors.
RGB = Red, Green, Blue
RGB additive model is "additive", because the combination of all colors together leads to white, black is the
absents of light.
See color tables in the internet:
www.tayloredmktg.com/rgb/
www.rapidtables.com/web/color/RGB_Color.htm
9. 2. Image
2.2 Technical parameters/color codes and digital representation of pictures
CMYK colors – substractive model
CMYK model (process colors, four colours) is used in color prints:
CMYK = cyan, magenta, yellow, and key (black)
CMYK model works through partly or complete color masking on a lighter, normally white background. Ink
(printing color) reduces light, which otherwise would be reflected. Such model is substractive because the
ink ”dissolves” luminosity from the with color.
Differently from RGB model the CMYK model works as follows: white is normal color of the paper or some other
background, black results from the addition of all colors. To save CMY colors and to achieve a deep black
color tone, black is often added as separate ink.
R
GB
Left: CMYK
model in
square
represen-
tation
Right:
(1) CMYC
substractive
model,
(2) RGB
additive
model
10. 2. Image
2.2 Technical parameters/color codes and digital representation of pictures
Layers of RGB model (left) and grey scales (right) examplified with GIMP logo.
Channels according to the particular color as well as with additional operational alpha channel
11. 2. Image
2.2 Technical parameters/color codes and digital representation of pictures
Image sensor
Its a device converting optical pictures into electronic signals. Its mostly used in digital cameras,
camera modules and other photographing devices. Earlier analogue sensors where video
camera tubes the newest are digital charge-coupled device (CCD) or complementary metal–
oxide–semiconductor (CMOS) sensors.
Digital cameras use photosensitive electronics (CCD or CMOS sensors), which consist of a big
number of single sensors, each of them saves the measures of intensity level. In most digital
cameras sensors are covered with a color filter (mosaic) of red, green and blue areas according
to the Bayer filter positioning in a way that eacg sensor element saves one concrete color
intensity. The camera interpolates the color information of the sensors through the process of
demosaicing and creates the final picture. Also this elements are sometimes called pixels, but
they have only on channel (only red, greenm blue).
Therefore each sensor's two out of three colors need to be interpolated and so called N-megapixel
camera, which produces N-megapixel picture, offer only 1/3 of the information which same size
picture or a scanned image.
12. 2. Image
2.2 Technical parameters/color codes and digital representation of pictures
Bayer filter
Bayer filter mosaic is the color filter array (CFA) in the square grid of the photosensor.
13. 2. Image
2.2 Technical parameters/color codes and
digital representation of pictures
Bayer filter
Bayer filter mosaic is the color filter array
(CFA) in the square grid of the
photosensor.
Picture above: camera reconstructing the
picture from the sensors' information using
interpolation.
Picture below: it shows how the Bayer filter
of the camera sees the picture without
interpolation process.