Multimedia- and Web-based Information Systems - PowerPoint PPT Presentation

1 / 48
About This Presentation
Title:

Multimedia- and Web-based Information Systems

Description:

Multimedia- and Web-based Information Systems Lecture 5 Multimedia: Color- and Video-technology Video-Technology Television- and Video-Technology form the basis of ... – PowerPoint PPT presentation

Number of Views:537
Avg rating:3.0/5.0
Slides: 49
Provided by: trA56
Category:

less

Transcript and Presenter's Notes

Title: Multimedia- and Web-based Information Systems


1
Multimedia- and Web-based Information Systems
  • Lecture 5

2
Multimedia Color- and Video-technology
3
Video-Technology
  • Television- and Video-Technology form the basis
    of the medium motion picture
  • Generation
  • Recording from the real world
  • Synthesis on the basis of a description
  • Analogous and digital technology

4
Representation of the video signal
  • Representation of the video signal contains
  • Visual representation
  • Transmission
  • Digitalization

5
Visual Representation
  • Presentation of the video signal trough a CRT
    (Cathode Ray Tube)
  • In television and computer screens
  • Representation of a scene as realistic as
    possible
  • Delivery of the space and time content of a scene

6
Fundamentals of visual representation
  • Resolution
  • Width W
  • Height H
  • E.g. W833, H625
  • Width/height-relation
  • 43 or 169
  • Perception of depth
  • In the natural preception trough the use of both
    eyes (different view angles onto one scene)
  • Focus-depth of the camera, appearance of the
    material of an object

7
Fundamentals of visual representation
  • Luminance / Chrominance
  • Motion picture resolution / continuity
  • Discreet sequence of single pictures can be
    perceived as a continually sequence
  • Boundary of motion picture resolution
  • 15 pictures/sec (video used 30 pictures/sec)
  • No boundary with acoustic signals

8
Fundamentals of visual representation
  • Flicker
  • With small refresh rate
  • Eg. 50 or 60 Hz
  • Full and half pictures (interlacing)

9
RGB Color Coding
  • RGB (Red Green Blue)
  • Additive color blend
  • Normalization of values (RGB1)

10
YUV Color Coding
  • For the human eye, brightness is more important
    than color information
  • Brightnessinformation (Luminance)
  • 1 channel of luminance (Y)
  • Color Information (Chrominance)
  • 2 channels of chrominance (U and V)

11
Component Coding YUV
  • Y 0.30 R 0.59 G 0.11 B
  • U 0.493 (B-Y)
  • V 0.877 (R-Y)
  • Errors in Y are more severe
  • Y to be encoded with high bandwidth
  • YUV Coding often specified with a raito of the
    channels (422)

12
Component Coding YUV
  • YIQ (similar to YUV)
  • Derived from NTSC
  • Y 0.30 R 0.59 G 0.11 B
  • I 0.60 R 0.28 G 0.32 B
  • Q 0.21 R 0.52 G 0.31 B

13
Shared Signal
  • Individual components (RGB, YUV, YIQ) need to be
    combined to one signal
  • Methods of modulation to avoid interference

14
Video formats
  • Resolution of a picture (frame)
  • Quantisation
  • Framerate
  • Video controller
  • Dedicated video memory

15
Video formats
  • CGA (Color Graphics Adapter)
  • 320x200, 4 colors, 16.000 bytes
  • EGA (Enhanced Graphic Adapter)
  • 640x350, 16 colors, 112.000 bytes
  • VGA (Video Graphic Array)
  • 640x480, 256 colors, 307.200 bytes
  • XVGA (eXtended Video Graphic Array)
  • 1024x768, 256 colors, 768.423 bytes
  • XGA (eXtended Graphic Array)
  • 1024x768, 16M colors, 2304 kbytes
  • Many more

16
Conventional Systems
  • NTSC (National Television Systems Commitee)
  • From the USA, oldest standard, widely used, 30
    Hz, 525 lines
  • SECAM (Sequential Coleur avec Memoire)
  • France, Eastern Europe, 25 Hz, 625 lines
  • PAL (Phase Alternating Line)
  • Western Europe, 25 Hz, 625 lines

17
High-Definition Television (HDTV)
  • Resolution
  • 1440x1152 / 1920x1152
  • Frame rate
  • 50 or 60 Hz
  • No longer interlaced

18
Digitalisation of video signals
  • Conversion into a digital representation
  • Nyquist-Theorem (bandwidth half the sampling
    rate)
  • Of the components
  • Quantisation
  • 2 Alternatives
  • Shared Coding
  • Component Coding

19
Shared Coding
  • Scanning of the whole of the analogue video
    signal (e.g. composite video)
  • Dependant on the standard
  • Bandwidth the same for all components
  • Disadvantage low in contrast

20
Component Coding
  • Separate digitalisation of the components (e.g.
    YUV)
  • Ratio 422
  • 864 scan values for luminance
  • 432 scan values for chrominancy

21
Digital Television
  • Digital Television Broadcasting (DTVB)
  • Digital Video Broadcasting (DVB)
  • DVB-T (terrestric broadcast)
  • System description
  • Implementation of HDTV
  • Employs MPEG-2
  • Coding of Audio and Video

22
Advantages of DVB
  • Increase in the number of TV-channels
  • Adaptable picture and sound quality
  • Encryption possible for Pay-TV
  • New Services Data broadcast, Multimedia
    broadcast, Video-on-Demand
  • Convergence of PC and TV

23
Multimedia Data Compression
24
Data Compression
  • Audio and Video require lots of storage space
  • Increasing Demand
  • Text Single Pictures Audio Motion Picture
  • Data rates influence
  • Transmission
  • Processing
  • Efficient Compression
  • Theory
  • Standards

25
Storage Space / Bandwidth
  • Considerable storage capacity for uncompressed
    pictures, audio and video data
  • For uncompressed Video, even a DVD is not
    sufficient
  • Uncompressed Audio-/Videodata requires very high
    bandwidth

26
Required Storage Space
  • Text
  • 80 x 60 2 bytes 9600 bytes 9,4 KByte
  • Figures
  • 500 primitives 5 Bytes for properties 2500
    bytes
  • Voice
  • 8 kHz, 8 bit quantisation 8 kByte / s
  • Audio
  • 2 x 4410016 bit / 8 bit 1 byte 172 Kbyte / s
  • Video
  • 640 x 480 3 x 25 frames 22,500 Kbyte /s

27
Important Methods
  • JPEG (JPEG 2000)
  • For single pictures
  • H.261 and H.263
  • Video sequences of small resolution
  • MPEG 1,2 and 4
  • Motion Picture and Audio (MPEG Layer 3)

28
Demands on Methods
  • Good quality
  • Small complexity
  • Effective implementation
  • Time boundaries with decompression (and
    compression)
  • MPEG-1 high effort with compression

29
Demands in Dialogue mode
  • End-to-End latency
  • Part of the (De-)Compression lt 150 ms
  • 50 ms -gt natural dialogue
  • Additionally all latencies of the network,
    communication protocols and of the in- and output
    devices

30
Demands in Query mode
  • Fast Forward / Rewind with simoultaneuos display
    of the data
  • Random access to single frames
  • lt 0.5 s
  • Decompression of single pictures without
    interpretation of all the frames before them

31
Demands in Dialogue and Query mode
  • Format independent of screen size and refresh
    rate
  • Audio and video in different qualities (to adapt
    to the respective circumstances)
  • Synchronisation of Audio and Video
  • Implementation in software

32
Classification of compression methods
  • Entropy coding
  • Lossless methods
  • Source coding
  • Often lossy
  • Hybrid coding
  • Combined application of both of the methods above
    for a specific scenario

33
Entropy coding
  • Independent of media specific properties
  • Data to compress is a sequence of digital data
    values
  • Losslessness
  • Data before and after the compression/decompressio
    n are identical

34
Source coding
  • Usage of the semantics of the information
  • Compression ratio depends on the specific medium
  • Data before and after the compressen/decompression
    are very similar to each other but no longer
    identical

35
Hybrid coding
  • Combination of entroy and souce coding, used e.g.
    In
  • JPEG
  • MPEG
  • H.263

36
Decompression
  • Inverse function of the compression
  • Decompression possible in real time?
  • Symmetric methods
  • Similar effort for coding and decoding
  • Assymetric method
  • Decoding possible with smaller effort

37
Run length encoding
  • Sequence of identical bytes
  • Number of repeating bytes
  • Mark M (e.g. !)
  • Stuffing if M is in the data space
  • Example 1 0, !, 256
  • Example 2 !, ! (Stuffing)
  • In what cases does it help? Maximum saving?

38
Suppression of null values
  • Special case of run length encoding
  • Selection of a single character that is repeated
    often (e.g. 0)
  • Mark M, after that number of repetitions
  • In what cases does it help? Maximum saving?

39
Vector quantisation
  • Splitting of the data stream into blocks of n
    bytes
  • Table with patterns for blocks
  • Index into the table to the entry most similar to
    the block
  • Multi-dimensional table -gt vector
  • Approximation of the original data stream
  • Example

40
Pattern Substitution
  • Patterns of frequent occurence replaced by one
    byte
  • Mark M, then index into a table
  • Well suited for text
  • e.g. keywords in programming languages

41
Diatomic Encoding
  • Putting together of two bytes of data at a time
  • Determination of the byte-pairs occuring most
    frequently
  • e.g. in the English language
  • E, T, TH, RE, IN, ... (8 in total)
  • Special bytes not occuring in the text used to
    represent 2 letters
  • Reduction in data of ca. 10

42
Static encoding
  • Frequency of occurence of a character
  • Different coding length for characters
  • Basis of the Morse code
  • Important unambigous decompression

43
Huffmann coding
  • Regards the probability of occurence
  • Minimum number of bits for given probability of
    occurence
  • Characters occuring most often get the shortest
    code words
  • Binary tree (Nodes contain probabilities, edges
    bit 0 or 1)

44
Huffmann coding
  • P(A)0.16, P(B)0.51, P(C)0.09, P(D)0.13 and
    P(E)0.11

45
Huffmann Coding
P(ADCEB)1.0
1
0
P(B)0.51
P(ADCE)
0
1
P(CE)0.20
P(AD)0.29
0
1
1
0
P(C)0.09
P(E)0.11
P(D)0.13
P(A)0.16
  • w(A)001, w(B)1, w(C)011, w(D)000, w(E)010

46
Transformation coding
  • Data transformed into a better suited
    mathematical space
  • Inverse Transformation needs to be possible
  • Discrete Cosine-Transformation (DCT)
  • Fast-Fourier-Transformation (FFT)
  • See example in the JPEG lecture

47
Prediction or relative encoding
  • Forming the difference to the previous value
  • Data do not differ much
  • Combination of methods
  • e.g. homogenous areas in pictures
  • DPCM, DM and ADPCM

48
Further Methods
  • Color tables
  • with pictures (video)
  • Muting
  • Threshold for sound volume
Write a Comment
User Comments (0)
About PowerShow.com