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Explore the backbone of multimedia products with a variety of graphics sources, tools, and file formats. Learn about bitmap and vector images, color systems, image editing, and 3D models.
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CHAPTER 05:GRAPHICS TECHNOLOGY :: Graphics Technology :: ~ Introduction ~ ~ Bitmap versus vector ~ ~ Colors system ~ ~ Image editing~ ~ 3-D image models ~
Graphics Technology • Introduction • Backbone of multimedia product. • There are many sources to present graphics; picture, image, clip art, etc. • Provide backgrounds, informational contents, and navigational controls. • Graphics are created using a variety of tools such as paint/drawing software, scanners, and digital cameras. • Graphics are stored in files in variety types of formats, depending on the size and quality.
Graphics Technology • Elements of graphics • Pictures versus images ??? Both are two levels of graphics abstraction. • Pictures are found in the world external to the computer while images are 2D representations of pictures found in computers. • Look and feel • Easy to store • Two basic approaches: Raster or bitmap images & Vector or metafile images.
Raster / Bitmap Images • The most common and comprehensive form of storage. • Looks as much as possible like the real-world or original product – accurate. • Created as 2D sets of points on a computer display (each point can display from two to millions of colours). • Points made up of a matrix of elements called pixels. • Really depends on hardware capability.
Raster / Bitmap Images • Where do bitmaps come from: • Make a bitmap from scratch with a paint or drawing program. • Grab from an active computer screen with a screen capture program, and then paste it. • Capture from a photo or artwork, using a scanner or digital camera or video capture device that digitizes the image
Raster / Bitmap Images • Technically characterized by • the number of bits per pixelor color depth or intensity level, which determines the number of colors it can represent • the width and height of the image in pixels or spatial resolution • Determine the quality and size of the images
Raster / Bitmap Images • Color depth (Intensity Level) • Colour depth is determined by how much data, in bits, is used to determine the number of colours. 1 bit yields 2 colours 4 bits yields 16 colours 8 bits (1 byte) yields 256 colours 16 bits (2 bytes) yields 65,536 colours 24 bits (3 bytes) yields 16,777,216 colours
Raster / Bitmap Images 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 00110011,01010101 16 65,536 1010101010101010
Raster / Bitmap Images Monochrome display: each pixel is most commonly set to black or white (1 bit) also called as a binary image
Raster / Bitmap Images • 8 bits per pixel allows 256 distinct colors BMP – 119KB
Raster / Bitmap Images • 16 bits per pixel represents 32K distinct colors (Most graphic chipsets now supports the full 65536 colors and the color green uses the extra one bit) BMP – 234 KB
Raster / Bitmap Images • 24 bits per pixel allows millions of colors BMP – 350KB
Raster / Bitmap Images • More bits provide more color depth, hence more photo-realism, • but require more memory and processing power • Graphics production software may capture in 24-bit color and convert to 8-bit
Raster / Bitmap Images This example zoomed in at 500% illustrates how several small pixels make up a raster image.
Raster / Bitmap Images • Spatial Resolution • Is a number of pixels and is related to the size of image file. • 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) 5.1 Megapixels
Raster / Bitmap Images 1024 Resolution
Raster / Bitmap Images 512 Resolution
Raster / Bitmap Images 256 Resolution
Raster / Bitmap Images 128 Resolution
Raster / Bitmap Images 64 Resolution
Raster / Bitmap Images 32 Resolution From your observation, what you can conclude by the number of resolution?
Determining Size of Raster Images • Size can be determined by multiplying the number of pixels (spatial resolution) in the horizontal plane (x) by the number of pixels in the vertical (y), then take this value and multiply it by the number of bytes per pixels (bit depth). • image size (bytes) = x * y * (bits per pixel/8) • Example: A standard computer VGA display is 640 X 480 pixels for a total of 307,200 pixels. A two-color or monochrome display image consists of 38,400 bytes.
Determining Size of Raster Images (cont) • Try these: A standard computer VGA display is 640 X 480 pixels for a total of 307,200 pixels … • 256-colour display images • 24-bit colour • The more colours used, the more bytes are required to encode the image, and the more bytes required for an image, the larger the file to store the image.
Raster Image Formats • The most common file formats for graphics across most computer platform. • Offer a very accurate reproduction of an image based on its colour depth and resolution. • Easiest files to import and export at any platforms of computers. • PNG • TIFF • GIF • JPEG/JPG • BMP, MacPaint, and XBM
Raster / Bitmap Images • Advantages: • Realistic images (high colour depth) • Easy to edit • Can be compressed • Disadvantages: • File size is too big • Take more processor times to generate the image • Suffers from distortion problem (replication of pixels elements)
Vector Images • Based on drawing elements or objects such as lines, rectangle, circles, etc. • Stored as commands that define the individual objects. • Scaling factor approach. • Advantages: • Small file size (less memory and disk usage). • Can be resized into larger image (no distortion problem) • Consists of a set of commands that are drawn when needed. • Easy to convert into bitmap format
Vector Images • Disadvantages: • Not realistic • Too many vector graphics on screen could increase processor time consumptions (too many mathematic functions must be calculated) RECT 0,0,200,200,RED,BLUE
Vector Image Formats • Are common across many operating systems and a number of vendor specific applications. • Example: Windows metafile is generated by processing vector commands by graphic functions in the Windows operating system. • Commands are processed as a series of records that are loaded and executed in sequence. • Clip arts
Vector Image Formats • Windows Metafiles
Vector Images Applications of vector drawn: i. Computer-aided design (CAD); for creating the highly complex and geometric renderings needed by architects and engineers ii. Graphics artists design; for printed media without “jaggies” iii. 3D animation program; for various changes of position, rotation, and shading of light (all must be calculated mathematically)
Image and its colors • Vital component of multimedia. • Picking right colours and combination of colours for multimedia involve many tries. • Eye’s receptors are sensitive to red, green, and blue. • Two basic methods of making color: • Additive color • Subtractive color
Computerized colors Additive Colour: • A colour is created by combining coloured light source in three primary colours: red, green, and blue (RGB) • Used for a TV or computer monitor • Electron beam • Combination creates all other colours
Computerized colors Subtractive Colour: • A colour is created by combining coloured media such as paint or ink that absorb some parts of the colour spectrum of light • Is the process used to create colour in printing • Made up of three primary colours: cyan, magenta, and yellow (sometimes black) - CMYK
Computer Color Models • Red, Green, Blue (RGB) Colour System: • This system divides the colour signal into three channels: red(R),green(G),and blue(B).It is based on combination of additive primaries to produce colour mixtures • Using 24-bit model, each red, green, and blue are set to a value of 256 choices (0-255) • Eight bits of memory is required (8+8+8 = 24) to describe about 16.7 millions of colours
Computer Color Models • Red, Green, Blue (RGB) Colour System: Red only (255,0,0) Red Green only (0,255,0) Green Blue only (0,0,255) Blue Red and Green, Blue subtracted (255,255,0) Yellow Red and Blue, Green subtracted (255,0,255) Magenta Green and Blue, Red subtracted (0,255,255) Cyan Red, Green, and Blue (255,255,255) White None (0,0,0) Black
Magenta Red Yellow White Black Blue Green Cyan RGB Color Models (0,0,0) = Pure black (1,1,1) = Pure white (1,0,0) = Pure red (0,1,0) = Pure green (0,0,1) = Pure blue (1,0,1) = Magenta
Computer Color Models HSB / HSL Colour System • Specifying hue or colour as an angle from 0 to 360 degrees on a colour wheel, and saturation, brightness, and lightness as percentages • Saturation is the intensity of a colour • At 100% saturation, a colour is pure; at 0% saturation the colour is white, black or grey • Lightness or brightness is the percentage of black or white that is mixed with a colour • A lightness of 100% will yield a white colour, 0% is black, and 50% is the pure colour
HSB Color Models • HSB Colour System: • Colour Degrees • Red 0° • Yellow 60 ° • Green 120 ° • Blue 240 ° • Magenta 300 ° Saturation Lightness & Brightness Hue
Green Cyan Blue Black White Yellow Magenta Red Computer Color Models CMYK Colour System • Is less applicable to multimedia production • Used primarily in the printing purposes (0,0,0) = Pure white (1,1,1) = Pure black Cyan + Yellow = Green
Image and its colors Colour Palettes • Computer manage colour via palettes or colour look-up tables, which are mathematical tables that define the colour of any particular pixel displayed and the total number of colours that can be displayed on a system. • Colour palettes are defined by indexing values correlated to red, blue, and green colours. The value ranges from 0 to 255. • Unique palette value. • When an image is displayed, its palette is mapped into the system palette.
Colour Palettes Colour-depth Colours Available 1-bit 2 colours (Black and white) 2-bit 4 colours 4-bit 16 colours 8-bit 256 colours (good enough for colour images) 16-bit 65,536 colours (excellent for colour images) 24-bit 16.7 millions colours (totally photo-realistic).
Computerized color Colour Dithering • Is a process whereby the colour value of each pixel is changed to the closest matching colour value in the target palette, using a mathematical algorithm. • Consider you have a scanned or digitised images that are captured at 24 bit, with 16 million of colour depth. • If this image is subsequently displayed on a computer monitor and system that is limited to less than 16 million colour depth (say 256 colours) the image must be transformed for display in the lesser colour palette.
Computerized color Colour Dithering • The image palette is mapped into the new palette dimensions with colours substituted with the closest available values. • The quality of dithering is depending on the algorithm used but most systems provide close approximations of the original