Lesson Objectives Aims You should be able to: Explain the representation of an image as pixels encoded in binary Explain the need for Metadata: Height Width Colour Depth Discuss the effect of colour depth and resolution on the size of an image file

File types A “file” is simply a huge binary dump It doesn’t matter whether you’ve saved an image, word document, music… it’s all just binary So how does the computer know what that binary is?! What kind of data is it?

The answer Several ways: Meta data: File types File headers Meta Data Extra information added to a file to describe its content, features and attributes. E.g. Resolution, encoding used, compression type, dimensions…

The amount of data in an image will be dictated by: Image size The amount of data in an image will be dictated by: The resolution (number of pixels in a given space) The colour depth The encoding method used The type of file and any meta data it stores (RAW vs JPG for example)

File Types Type Common File Types Lossy/Lossless Compressed? Images JPG Lossy Yes GIF BMP Lossless No PNG Sound WAV MP3 FLAC Text TXT N/A DOCX RTF Video MPEG MP4 MOV

June 2015 – Q2

Compression Files, especially music and images, can get very, very large This introduces the need for compression Compression: Reduces the FILE size Removes unnecessary information The file can still be reproduced even the size has reduced Can be Lossy or Lossless

Compression Lossless Lossy The file size is reduced but no quality/information is lost The file can be reproduced exactly No compromise – file size reduced but quality/content unaffected Should result in a reduction in file size but may not be significant Lossy The file size is reduced but information/quality IS lost A trade off between quality and file size Only acceptable in certain situations Images Sound Video

June 2013 – Q8

Meta Data is usually included in image files to indicate: The dimensions (width, height) The type of compression used The colour depth of the image Can contain lots of detail – EXIF…

Encoding All pictures are made up of pixels

The number of pixels in an image or on a screen is it’s “Resolution.” E.g. HD TV = 1920 x 1080 = 2,073,600 pixels per image. This explains why there is a need for compression – images contain a LOT of data! Important – resolution is a measure of pixels in a given space (the concentration). 1920x1080 will look amazing on a 15” display and awful on a 60” display – why?

Each pixel can then be “encoded” to represent its colour. Colour is made on computers by mixing different amounts of Red, Green and Blue

The number of bits used to represent each colour will determine the “colour depth” of the image This is the number of colours that can be displayed – and will affect the quality or “realism” of the final image.

Colour Depth 1-bit colour (21 = 2 colours): monochrome, often black and white, compact Macintoshes, Atari ST. 2-bit colour (22 = 4 colours): CGA, gray-scale 4-bit colour (24 = 16 colours): as used by EGA and by the least common denominator VGA standard at higher resolution, 8-bit colour (28 = 256 colours): most early colour Unix workstations, VGA at low resolution, Super VGA 16 - Bit 24 - Bit 32 - Bit

Colour Depth

At its most basic, we can encode an image simply as a stream of bits: Encoding At its most basic, we can encode an image simply as a stream of bits: =1,0,0,0,0,0,1,0 =0,1,0,0,0,1,0,0 =0,0,1,0,1,0,0,0 =0,0,0,1,0,0,0,0

Because of the amount of repetition, we can compress this using “run length encoding” – one example of lossless compression. =1,5,1,1 =1,1,3,1,2 =2,1,1,1,3 =3,1,4

Specimen Paper

Jan 2012 – Q5

Further exam questions Jun-13 Compression 8a May-11 3c Jun-15 Compression - Lossy and Lossless 2b 8b Jun-15 File types 2a Jun-14 4c Jan-13 2 May-12 File Types 4 May-11 3b Jan-12 File Types - Bitmaps 5