2. Data Representation - Multimedia

Question 1

How do we perceive sound?

Answer 1

Series of air compression vibrates membrane in our ear –> sends signal to our brain

Question 2

How does a stereo work?

Answer 2

Sends electrical signal to a speaker to produce sound

Question 3

What is the signal in sound representations?

Answer 3

Analogous representation of sound wave

Question 4

How do we digitize sound signal?

Answer 4

Sample sound periodically –> measure voltage –> record the numeric value

Sample rate of 40 000 times per second needed for reasonable sound

Question 5

Audio Formats

Answer 5

WAV
MP3

Based on storage of voltage values sampled from analog signals

Question 6

How do we perceive colour?

Answer 6

–> detect frequencies of light that reach the retinas of our eyes

–> retinas have 3 types of colour photoreceptors –> RGB

Question 7

RGB

Answer 7

Values indicate the relative contribution of each of the primary colours

Question 8

Colour depth

Answer 8

Amount of data used to represent per pixel

High colour –> 16 bit col depth:
-5 bits per RGB
-extra bit can represent transparency

True colour: 24 bit representation
- 8 bits per RGB

Question 9

Representing graphics

Answer 9

Photo –> analogue rep of an image

Digitization: pixels used to rep an image

Question 10

Raster Graphics

Answer 10

Stores data on pixel-by-pixel basis

BITMAP: contains pixel colour values of the image from left to right and top to bottom

GIF: limits number of colours per image to 256

JPEG: averages out colour hues over short distances

PNG: like GIF but achieves greater compression with wider range of colour depth values

Question 11

Vector Graphics

Answer 11

Describes images in terms of lines and geometric shapes

Images created directly from geom. shapes that are defined on cartesian plane (points, lines, curve…)

Not every pixel is described –> smaller file size

Two formats:
1) Adobe & Flash
2) Scalable Vector Graphics (SVG)

Advantage: can be resized mathematically

NOT GOOD for representing real world images

Question 12

Types of redundancy in digital image

Answer 12

1) Coding redundancy

2) Inter-pixel Spacial redundancy

3) Inter-pixel Temporal redundancy

4) Psychovisual Redundancy

Question 13

Coding Redundancy

Answer 13

Grey levels of an image are coded using more code symbols than necessary

Question 14

Inter-pixel Spacial Redundancy

Answer 14

Due to correlation between the neighboring pixels in an image

Question 15

Inter-pixel Temporal Redundancy

Answer 15

Statistical correlation between pixels from successive frames in a video sequence

Question 16

Psychovisual Redundancy

Answer 16

We do not perceive images by analysing every pixel in an image

Question 17

JPEG

Answer 17

Standard for saving images

Question 18

Factors determining video file size in relation to quality

Answer 18

1) Time : longer = bigger files

2) Number of pixels (resolution) –> larger = bigger files

3) Frame rate: higher = bigger files

4) Amount of motion in the video: more = bigger files

Question 19

Spatial Compression

Answer 19

Removes redundant information within a frame

Question 20

Temporal Compression

Answer 20

Aims to reduce differences between consecutive frames

Question 21

Frame types

Answer 21

1) Intra-coded frames (I-frames)

2) Predicted frames (P-frames)

3) Bi-directional frames (B-frames)

Question 22

Reference Frame

Answer 22

Frame used as a reference for predicting other frames

Question 23

I-Frames

Answer 23

Frame that is encoded with no reference to other frames

Have the least amount of compression

Question 24

Predicted Frames

Answer 24

Encoding based on preceding I or P frame –> helps save bits

–> risk is error propagation

Question 25

B-frames

Answer 25

Inter-coded, Interpolation frames

saves even more bits than P

Used to combat fast moving objects

Question 26

Macroblocks

Answer 26

Pictures (frames) usually segmented into macroblocks

Individual prediction types can be selected on a macroblock basis rather than being the same for the entire picture