Chapter 1: Information Representation

Base 16, from 0-9 to A-F

- In MAC and IP Addresses
- Represent Colours in HTML
- In error messages and memory dumps

Kibi (Ki) = 1024 bytes
Mebi (Mi) = 1024 KiB
Gibi (Gi) = 1024 MiB
Tebi (Ti) = 1024 GiB

Kilo (k) = 1000 bytes
Mega (M) = 1000 Kb
Giga (G) = 1000 Mb
Tera (T) = 1000 Gb

Number system that uses 4 bits to represent each denary digit.
e.g:
- (19 in BCD): - 00011001
- 0001 (= 1) 1001 (= 9)
- 19

- Used to represent numbers in calculators and counters
- Allows you to accurately measure fractions
- Electronically code decimal numbers

ASCII, Extended ASCII, Unicode

American Standard Code for Information Interchange
- 128 characters
- Only from the English language
- 7 bits

- 256 characters
- Most European langauges including English
- 8 bits

- 10,000 characters
- variety of languages
- current standard
- 32 bits

The smallest unit of area in an image representing a single colour

Stores data about the image,
- Size
- Resolution
- Colour depth
- Number of colours

Number of pixels wide by the number of pixels high

Number of bits used to represent the colours in a pixel

Number of bits used to represent the smallest unit in an image file (or sound file);
- The larger the bit depth, the better the quality of the sound or colour image.

File size = (Width x Height x Bit depth (in bytes)) + Header bytes

- Reducing bit depth, fewer bits used to store each pixel in an image
- Reducing colour palette, less colours and therefore less bits per pixel
- Reduced image resolution, fewer pixels per unit area so less space is needed

Using Run Length Encoding (RLE), - Looks for a series of consecutive pixels that store the same colour,
-- Indexes the colour and the number of times it occurs.

- Reduce amplitude to only the range used, limited amplitudes mean fewer bits per sample
- Run-length-encoding, Where consecutive sounds are the same record the binary value of the sound and number of times it repeats
- Record the changes instead of the actual sounds

Images using 2D points to describe lines and curves and their properties; grouped to form geometric shapes

- Can be scaled without losing quality as it gets recalculated.
- Relatively small file size, stores equations not pixels.

The number of bits used to store each sample.
- Larger values mean more accurate reconstruction of sound but higher file size (more bits used to store the sound)

The number of samples taken per unit time

Sound size = sampling rate x sampling resolution x time

Continous real-world data

Discrete electrical data

The reduction of file size

- Reduces transfer time
- Saves bandwidth
- Saves storage space

Lossy and Lossless

File size compression where original data is lost and cannot be recovered

File size compression where original data is not lost and can be recovered

- Maintains quality
- Useful when all original data needs to be recovered

Pros:
- Creates a much smaller file size than lossless
-- Useful when significant size reduction is needed
Cons:
- Significant loss in quality