Notes-for-CAIE

1.1 Information representation

1.1.1 Binary representation

Why use binary to represent data[1]:

• Any electronic device can only read signals in 2 discrete states which are on or off, which is represented by a 1 or 0

1.1.2 Image

• show understanding of how data for a bitmapped image is encoded
• use the terminology associated with bitmaps: pixel, file header, image resolution, screen resolution
• perform calculations estimating the file size for bitmapped images of different resolutions
• show understanding of how data for a vector graphic is represented and encoded
• use the terminology associated with vector graphics: drawing object, property and drawing list
• 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 g

Pixel: the smallest picture element which can be drawn

Image Resolution: the amount of pixels per centimeter

Screen Resolution: the number of pixels which can be viewed horizontally and vertically on the screen

Color Depth: number of bits used to represent the color of a single pixel

Bitmap[3]:

• Made up of pixels;
• Each pixel has one color;
• Each colour has an unique binary number
• Color of each pixel stored as a binary number;

Using Vector graphic than bitmap graphic:

• • Benefit: Can resize it without pixilation
  • Reason: Image is calculated with each adjustment
• • Benefit: Smaller file size
  • Reason: It stores command, not pixels.

Bitmap and Vector graphic

w16 11 Q7 [4]

• Bitmaps made up of pixels
• Vector can resize…
• Bitmaps are usually bigger than graphic
• Bitmaps are suitable for photographs
• Bitmaps use less processing power

1.1.3 Sound

• show understanding of how sound is represented and encoded
• use the associated terminology: sampling, sampling rate, sampling resolution
• show understanding of how file sizes depend on sampling rate and sampling resolution
• show understanding of how typical features found in sound editing software are used in practice

Sampling: amplitude of sound wave taken at different points in time

Sampling Resolution: number of bits assigned to each sample

Sampling Rate: number of samples taken per unit time

Bit rate: number of bits used to store 1 second of sound

How sound is recorded(sampled) [3]:

• Sound wave is sampled at a regular interval
• Each sample is stored as a binary number
• Samples are stored in order in a file

Using a higher sampling resolution [2]:

• Benefit: allows for larger dynamic range[1]; more accurate representation[1]
• Drawback: bigger files occupies more storage; grater processing power needed[1]

Difference between Loss-less and Lossy[3]:

• Lossless is designed to lost none of the original detail [1];
• Lossless technique is based on some form of replacement [1]
• Lossy may result in loss of detail compared to original file [1]
• (take examples of file formats or compressing techniques) [1-2]

When justifying why using lossy or loss-less, always:

• Consider ‘noticing’, e.g.: some loss of quality will not be noticed
• Consider bandwidth requirement
• Consider if quality or complete file is being required

1.1.4 Video

• Show understanding of the characteristics of video streams:
  • the frame rate (frames/second)
  • interlaced and progressive encoding
  • video interframe compression algorithms and spatial and temporal redundancy
  • multimedia container formats

Bit Streaming: On-demand; Real-time

Multimedia container format: the wrapper that contains various different types of data.

How it is possible to watch the video without continually pausing[4]:

• User needs high bandwidth [1];
• Data is streamed into a buffer which stops the video from pausing[1]:
• As buffered is empties, it fills up again so that the viewing is continuous[1];

Progressive Encoding [2]:

• Each frame contains the complete image
• Displays all the frame data at the same time
• The rate of picture display is the same as the frame rate
• High bandwidth requirements

Differences between Interlaced Encoding and Progressive Encoding:

Progressive	Interlaced
each frame contains the complete image	each frame contains half of the complete image
frames are not divided into fields	each frame divided into two fields
complete frames are displayed in sequence	data from two frames is displayed simultaneously
has high bandwidth requirements	halves the transmission bandwidth requirements

Interlaced Encoding [3]:

• Single frames are divided into separate fields:
• One field has data for odd numbered rows, another has data for even numbered rows.
• Odd numbered row fields alternate with even numbered row fields
• Viewers see the divided fields simultaneously

How the video is sent using bit streaming

• Data is compressed before transmitting
• The video is transmitted continuously as a series of bits
• On download, the buffer stores the data from the server
• The user’s software receives bit stream from the buffer

Redundancy

Temporal redundancy: Pixels in a sequence of consecutive video frames have the same value in the same location

Spatial redundancy: A sequence of consecutive pixels in a single video frame have the same value

Reduce Temporal Redundancy [2]:

• Identify the pixels that do not change between frames;
• Records only the differences between frames

1.1.5 Compression techniques

• show understanding of how digital data can be compressed, using either ‘lossless’ (including runlength encoding – RLE) or ‘lossy’ techniques

Lossless Compression: type of compression that allows original data to be perfectly reconstructed from compression

​ Run-length Encoding: compression in which sequences with same data value in many consecutive values are stored as a single data value and count

Lossy Compression: Data is lost; Decompressed file is not the same as the original

​ Perceptual coding: works by reducing certain parts of a sound which are less audible to human hearing

How one character is represented in a character set

Each character is represented by a unique binary number

How run-length encoding compress an image

w18 13 Q1.(c) [3]

• Looks for runs of consecutive pixel of the same colour
• Stores the colour value once and the number of times it occurs
• Lossless
• Examples