1.1 Information Representation

1.1.1 — Number representation

1.1.2 — Images

1.1.3 — Sound

1.1.4 — Video

1.1.5 — Compression techniques

1.1.1 Number representation

Show an understanding of the basis of different number systems and use the binary, denary and hexadecimal number system
Convert a number from one number system to another

Binary (base 2) - powers of 2

uses 1s and 0s to store data in digits
digits are ordered from right to left (1, 2, 4, 8, 16, etc)
encoding that has 4 digits are called ‘4 bit

Denary (base 10)

ordinary counting: 1 to 10
binary to denary
- e.g: 0001 1100 becomes 16 + 8 + 4 = 28

Hexadecimal (base 16)

aka ‘hex’, uses 0 to F
takes 4 bits of binary and converts to a single hex character
decimal 10 and above becomes A, B, C etc
- e.g: 0011 1101 becomes 3(13) which is 0x3D

Express a positive or negative integer in two’s complement form

Two's complement notation

If a binary sequence is notated as ‘two’s complement’, the left most bit determines the sign.

e.g: 0011 0011 is 32 + 16 + 2 + 1 = 51

whereas e.g: 1011 0011 becomes -128 + 32 +16 + 2 + 3
- = -128 + 51
- = -77

Show understanding of, and be able to represent, character data in its internal binary form depending on the character set used: ASCII and Unicode

ASCII

Also known as American Standard Code for Information Interchange.

4 bit encoding
Note: the first 128 characters are the same as UTF-8

Extended ASCII

extends to 8 bit (256 characters)

Disadvantages

not all characters can be represented by ASCII
in extended ASCII, the characters from 128 to 255 may be coded differently in different systems

UTF-8 / 16

UTF-16 is used to store a greater variety of characters i.e from different languages

Encoding for ‘A’

Hex: 0x41
Binary: 0100 0001
Denary: 65

Encoding for ‘n’

Hex: 0x6E
Binary: 0110 1110
Denary: 110

Express a denary number in Binary Coded Decimal (BCD) and vice versa
Describe practical applications where BCD is used

BCD (binary coded decimal)

represents each individual digit of a denary number (1, 2, 3 etc) with 4 bits
used in digital clock displays to store single digits: [ 5 ][ 4 ][ 1 ]

Encoding 64 in BCD

6 becomes 0110
4 becomes 0100

so 64 is 0110 0100 in BCD

1.1.2 Images

Show understanding of how data for a bitmapped image is encoded

Bitmap image encoding

Bitmaps

Bitmap data is encoded by assigning each pixel a binary value
Common bitmap (raster graphics) image file types:
- PNG
- JPG (JPEG)
- GIF

Colour depth

the amount of bits for encoding colour
- the more bits, the more available colours
most computers have 24-bit colour

e.g: 8-bit colour has 2⁸
- = 256 available colours

Use the terminology associated with bitmaps: pixel, file header, image resolution, screen resolution

Bitmap terminology

File header

this identifies the image format, palette, dimensions, etc.

Metadata

info on author, date or location of shot / creation, etc.

Image resolution

refers to the number of pixels in the image e.g: 1920 x 1080
can be changed

Screen resolution

refers to the number of pixels on the display
can be changed, though the native (original) resolution is fixed

Perform calculations estimating the file size for bitmapped images of different resolutions

Bitmap file size calculation

Example question 1

Calculate the file size of the image if:

The image colour depth is 8-bit
The image resolution is 900x600

Working:

8-bit colour depth means there are 2⁸ = 256 colours

There are 900x600 = 540000 pixels

So 8-bits are dedicated to each of the 540000 pixels
This means there are 8 * 540000 bits
- = 4320000 bits
- = 540000 bytes
- = 540 kilobytes

Example question 2

Calculate the time taken to transfer an image if:

The image colour depth is 24-bit
The image resolution is 1600x900
The transfer speed is at a rate of 1 kilobyte per second

Working:

24-bit colour depth means there are 2²⁴ = 16777216 colours

There are 1600x900 = 1440000 pixels

So 24-bits are dedicated to each of the 1440000 pixels
This means there are 24 * 1440000 bits
- = 34560000 bits
- = 4320000 bytes
- = 4320 kilobytes
4320 KB / 1 KBs^-1
- = 4320 seconds

Show understanding of how data for a vector graphic is represented and encoded
Show understanding of how typical features found in bitmapped and vector graphics software are used in practice
Justify where bitmapped graphics and/or vector graphics are appropriate for a given task

Vector graphic encoding

uses coordinates (lines) and geometry (shapes) to precisely draw parts of an image
- used for logos and icons - not suitable for realistic pictures

smaller than bitmaps as they do not encode pixel by pixel
can be scaled without losing resolution
- however, redrawing (recalculation) requires more processing power

uses SVG (scalable vector graphics) format

Use the terminology associated with vector graphics: drawing object, property and drawing list

Vector graphic terminology

Drawing object

a continuous vector path consisting of several points or vertices
- e.g: a circle or ellipse

Property

styles / appearances for the object
- e.g: fill, colour, gradient or pattern

Drawing list

an organised list of all the individual objects
- e.g: all objects displayed in a palette list

1.1.3 Sound

Show understanding of how sound is represented and encoded

Sound encoding

Representation

Sound is represented as waves, meaning they have:

frequency (pitch)
amplitude (loudness)

Encoding

A sound encoder has 2 components:

Band limiting filter

filters out high-frequencies we can't hear

Analogue-to-digital converter (ADC)

converts analogue signals to binary code

Use the associated terminology: sampling, sampling rate, sampling resolution
Show understanding of how file sizes depend on sampling rate and sampling resolution

Sound encoding terminology

Sampling

the process of converting analogue signals into digital

Sample rate

the duration / interval at which the sound is sampled

Sampling resolution

this is the number of bits dedicated to storing the amplitude
- more bits → higher quality

How sample rate and resolution affect file sizes

Whenever we increase the quality, meaning the:

Sample rate - number of times sampled per second
Sampling resolution - number of bits per degree of loudness

The file size increases as a result, because we are storing more information about the sound in the form of bits.

Show understanding of how typical features found in sound editing software are used in practice

Sound editing software

This type of software typically have features for:

combining sound waves
fading in and out
removing noise and imperfections

Applications

These features can be applied in:

combining - multitrack music
fade - easier to listen to
noise - removing background sound

1.1.4 Video

Show understanding of the characteristics of video streams:
- the frame rate (frames/second)
- interlaced and progressive encoding

Video stream

This is the transmission of video data continuously.

Frame rate

the number of frames displayed per second
- frames are still images that are played consecutively to form a video

Interlaced and Progressive encoding

These are illusionary methods of making a video appear to have a high refresh rate.

Interlaced

each frame is split into two halves:
- odd numbered lines
- even numbered lines

the first half is first displayed
once completed, the second half follows, this cycle is repeated

Progressive

requires high bandwidth (as large amounts of data is needed)
unlike interlaced encoding, each frame is displayed in full
- motion appears smoother and more realistic
- allows easier scaling to higher resolutions

Show understanding of the characteristics of video streams:
- video interframe compression algorithms and spatial and temporal redundancy

Interframe compression

A video compression codec (an encoder and decoder) compares each frame to the previous one. The codec sends only the differences to the reference frame.

Scenarios

Areas with no movement

the system sends a short command
the codec copies these parts into the next frame to save space

Sections move in a simple manner

the system sends a longer command
the codec shifts, rotates, lightens, or darkens the copy

Spacial / Temporal Redundancy

Redundancy

the amount of wasted space when compressing digital images

Spacial redundancy

when there are duplicated elements - like pixels
- we can compress them together

Temporal Redundancy

when there are similarities between each frame and the previous

Show understanding of the characteristics of video streams:
- multimedia container formats

Multimedia Container Formats

These are file formats which describe how the data and metadata in a file work.

Simpler container formats can contain different types of audio formats
More advanced container formats can support multiple audio and video streams, subtitles, chapter-information, etc.

1.1.5 Compression techniques

Show understanding of how digital data can be compressed, using either ‘lossless’ (including run-length encoding – RLE) or ‘lossy’ techniques

Lossless compression

This is a form of data compression that allows the original data to be perfectly reconstructed from the compressed data.

Run-length encoding

a lossless compression method which a run (sequence) of data is stored as a series of values carrying:
1. pixel value
2. repeat count

e.g: w w w t t t t q q q r q
would become:
- w 3 t 4 q 3 r q

Lossy compression

Also irreversible compression, in which data is discarded for the sake of reducing space. The original data may not be reconstructed perfectly.

Audio

lossy compression may be used to remove sounds that cannot be heard by the human ear

Images

lossy compression may be used to remove details which would be unnoticeable by eye
- e.g: reduce colour depth

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