image composition and compression

8/2/2019 Image Composition and Compression

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Digital Art


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Image files are composed in 2 ways: Raster (pixel) Vector (geometric) data


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Mostly used in Photoshop

Composes images by a grid (columns and rows)

Each pixel consists of numbers representingmagnitudes of brightness and colour


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More pixels = Higher resolution; clearer imagesformed

Less pixels = Lower resolution; blurrier imagesformed


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Mostly used in Illustrator

Uses geometrical primitives such as points, lines,curves, and shapes or polygons to form

mathematical equations

Represent images in computer graphics

Keeps resolution the same even when scaled


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Geographic location of each cell is implied by itsposition in the cell matrix

Other than an origin point, no geographiccoordinates are stored

Therefore, data analysis is usually easy to programand quick to perform


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Ideally suited for mathematical modeling andquantitative analysis

Discrete data is accommodated equally well ascontinuous data facilitates the integrating of thetwo data types

Grid-cell systems are very compatible with raster-based output devices


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Cell size determines resolution at which data isrepresented

Difficult to represent linear features depending onthe cell resolution; network linkages are difficult toestablish

Since most input data is in vector form, data mustundergo vector-to-raster conversion


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May lead to generalisation and choice ofinappropriate cell size

Most raster output maps do not need high clarity


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Data can keep its original resolution and formwithout generalisation No pixelated imagesformed

Graphic output is usually more aestheticallypleasing

No data conversion needed as most data are invector (e.g. Hard copy maps)


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Accurate geographic location of data ismaintained

Allows for efficient encoding of topology


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Location of each vertex needs to be storedexplicitly; leads to large data size

For effective analysis, vector data must beconverted into a topological structure

Requires extensive data cleaning after conversion


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Topology is static; any updating of data requires re-building of the topology

Algorithms for manipulative and analysis functionsare complex; lead to intensive processing

Limits functionality for large data sets (e.g. a largenumber of features)


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Continuous data is not effectively represented invector form

Spatial analysis and filtering within polygons isimpossible


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Uses algorithms to decrease size file

2 types of image file compression algorithms: Loseless Lossy


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Reduces file size without losing image quality

Unable to compress a file as small as lossycompression file

Chosen when image quality is valued above filesize


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Takes advantage of the inherent limitations of thehuman eye and discards invisible information

Allows variable quality levels (compression)

Compression levels increased = File size reduced

At high levels of compression, image deteriorationbecomes noticeable


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The detail that an image holds

Applies equally to digital images, film images, andother types of images

Higher resolution = More image detail

Resolution can be measured by how close linescan be to each other and still be seen


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Resolution units can be measured by physical sizes(e.g. lines per mm, lines per cm, etc.)

Line pairs are often used instead of lines

A line pair is a pair of adjacent dark and light lineswhile lines counts both dark lines and light lines


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A resolution of 10 lines per mm means 5 dark linesalternating with 5 light lines, or 5 line pairs per mm

Photographic lens and film resolution are mostoften quoted in line pairs per mm

TV lines refer to lines per picture height


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There are many types of resolutions but you will onlylearn about the two common ones

They are: Pixel resolution Temporal resolution


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An image of N pixels high by M pixels wide canhave any resolution less than N lines per N TV lines

The format for resolution is to describe the width bythe height of the overall image; e.g. 640 by 480

Another way to describe the resolution is to givethe number of megapixels


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It is calculated by width X height and 1 million

These resolution are not accurate as they just serveas an order on image resolution

Pixel columns means width

Pixel rows means height


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Movie cameras and high-speed cameras canresolve events at different points in time

The time resolution used for movies is usually 15 to30 fps

High-speed cameras may resolve 100 to 1000 fps,or even more

Many cameras and displays offset the colorcomponents relative to each other or mix uptemporal with spatial resolution:


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Many cameras and displays offset the colorcomponents relative to each other or mix uptemporal with spatial resolution:

Digital camera(Bayer color

filter array)

LCD (Triangularpixel geometry)

CRT (shadow mask)


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There are three main colour-encoding systems: PAL (Phase Alternating Line) NTSC (National Television System Committee) SECAM (Squentiel couleur mmoire, French

for "Sequential Color with Memory)


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Analog

350240 (260 lines): Video CD 330576 (250 lines): Umatic, Betamax, VHS,

Video8

400576 (300 lines): Super Betamax, Betacam(pro)


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Analog

440576 (330 lines): analog broadcast 560576 (420 lines): LaserDisc, Super VHS, Hi8

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576 (500 lines): Enhanced DefinitionBetamax


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Digital:

720576 (520 lines): D-VHS, DVD, miniDV, Digital8,Digital Betacam (pro)

720576 (400 lines): Widescreen DVD(anamorphic)

1280720 (720 lines): D-VHS, HD DVD, Blu-ray,HDV (miniDV)


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Digital:

14401080 (810 lines): HDV (miniDV) 19201080 (1080 lines): D-VHS, HD DVD, Blu-ray,

HDCAM SR (pro)

10,0007000 (7000 lines): IMAX, IMAX HD,OMNIMAX

image composition and compression

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