1. 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

2. 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?

3. 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…

4. 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)

5. 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

6. June 2015 – Q2

7. 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

8. 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

9. June 2013 – Q8

12. 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…

13. Encoding
All pictures are made up of pixels

14. 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?

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

16. 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.

20. 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

21. Colour Depth

22. 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

23. 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

24. Specimen Paper

26. Jan 2012 – Q5

28. 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