<<

1

coding

5.9. Compression Compression Video 5.9. (1) interframe

and

motion motion prediction/estimation, , block intraframe

according according peculiar to the videoconferencing,conditions, e.g. applications such as broadcast video matching  video compression and standards are distinguished carried only once wanted: strategies to exploit temporal redundancy and irrelevance!  assumption: successive images of a video sequence are similar, directly e.g. adjacent images contain almost the same information to be that has video time sequence := of single images frequent point of view: video compression image = compression temporal with a component

    

Basics:

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof. 

2

quantizer

coding

interframe

Video Compression (2)Compression Video coding, color subsampling 4:1:1, 6 6 bit subsamplingcoding, color 4:1:1,

compression of a time sequence of images based on the sequence of images a time ofcompression

JPEG - hardware solutions hardware possibility synchronize audio is not provided to data position every time full images at direct access to application and video softwarein proprietary consumer cutting temporal redundancy is not used! istemporal redundancy not 20:1, to 5:1 applicable compression ratios from for call higher for rates unfortunately, not standardized! unfortunately, JPEG, of baseline system the use of makes intraframe M JPEG standard

       

Simple Simple approach:

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof. 

3 -

head texture

, e.g. , e.g. and elements

motion

(3)

picture

the

: objects of

geometric

of

of

:

position describing

of

relations

of camera

processing deformation

, ,

of techniques

change compensation Compression

/ prediction

parameters

ranges

shadows semantic objects scaling

or , , zoom )

and no

and based values

model

prediction but video prediction

: Video Video

( pixels

4 rotation rotation , with -

color lights , , of of

arrangements region -

of of

based or

motion motion

model

of of prediction

information e.g. MPEG neighbouring model grid shoulder object extraction change translation change translation prediction • • • • • • • kinds kinds

 

Motion Motion

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof. 

4

Video Compression (4)Compression Video

little change in the contents of the image from one frame to the next one frame image from the contents of in the little change one from change do not image the of portions significant even if,

transmitted. Objects tend to move between frames! move between Objects tend to to be needs that information of amount the increase would We assumptions: - - next frame to the • • • encoding)? Solution: same the value of the at value a pixel by the Predict the of (differential difference location encode the and previous framein a use a previous frame to generate prediction for the next the prediction generate for to previous frame use a Block matching: No!

   

Motion prediction and compensation: (cont.) compensation: and prediction Motion

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof. 

5

(5)

Compression

Video Video Block (cont.)matching:

 Motion prediction and compensation: (cont.) compensation: and prediction Motion

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof. 

6

and is and

MxM

uncompensable

Video Compression (6)Compression Video that most closely matches the block being encoded beingthe block matches closelythat most

MxM previous reconstructed frame (reference image) is greater than some some is greater than image) (reference reconstructed frame previous is declared the block threshold, predefined of prediction. benefit without the encoded block being of the the difference the threshold, is below If the distance a transmitted. Additionallyand to its closest block is encoded encoded is transmitted. motion vector divide the frame being encoded into blocks of equal size size blocks of equal into encoded frame being the divide of the block for reconstructed frame search a previous for each block: size measure? closest block in a to the encoded block being of the If the distance • • • • Forward Forward prediction: 

Motion prediction and compensation: (cont.) compensation: and prediction Motion Block matching: (cont.)

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.

 

7

.)

cont (7)

: (

compensation Compression

.) and

cont : ( Video Video matching prediction Block

 Motion Motion

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof. 

8

Video Compression (8)Compression Video Block (cont.)matching:

 Motion prediction and compensation: (cont.) compensation: and prediction Motion

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof. 

9

Video Compression (9)Compression Video

objects moving in different increases different positions in moving objects prediction in poor can result to restrict block for search region matching to miss a match probability the increases more computations per comparison but fewer blocks per per frame but blocks fewer comparison per more computations of covering the probability size block increasing with major drawback:      reduce search space: reduce increase size of the blocks: of size increase • • "find closelymatching block" of requires large amount computation! Block (cont.)matching: Search strategies:

 

Motion prediction and compensation: (cont.) compensation: and prediction Motion

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof. 

10

general general video compression encoding /

Video CompressionVideo (10)

Block diagram: Block procedure

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof. 

11

4 part 2" 4 part - 1) were specific 1) were developed for -

4 / H.264) were developed H.264) wider range for 4 / -

standards: e.g. "H.263.1" or "MPEG "H.263.1" e.g. standards: -

x series - Video Compression OverviewCompression Video

new standards (MPEG new standards application of both define sub both define MPEG (H.261 / early standards purposes ITU: H.26x series ITU: H.26x MPEG ISO:

    

Two organizations Two

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof. 

12

H.261 / H.263(1)

-

Video CompressionVideo start / stop playingvideo start / stop restart of video play for automatic + timeoutimage freeze a still ... • • • control commands from encoder to decoder to encoder from control commands error correction information correction error bit) H.263: 8 bit / image sequence 5 (H.261: number Compressed data stream: p* 64 Kbit/s, p= 1, ..., 30 ..., 1, p= 64 Kbit/s, p* Compressed stream: in real time, symmetric procedure Compression symmetric in real time, ISDN to Targeted      

The data stream stream more information data structure The contains video: just than Video compression conferences video for compression Video

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.

 

13

H.261 / H.263(2)

-

CIF) -

Video CompressionVideo 704 x 576 1408 x 1152 4CIF (4 time CIF) 16CIF (16 times CIF) 128 x 96 176 x 144 (Sub Quarter CIF) SQCIF CIF (Common CIF (Common Intermediate Format) (Quarter QCIF 352 x 288 Video Video input must provide 29,97 images per second YUV representation with color sampling ratio of 4:2:0        

Decoders must implement rest only, QCIF is optional the H.263 only: Image sizes: Image preparation: Image

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.

 

 

14

changed

be

V plane V

may

and only

U

of

factor -

0,0) ) H.263): Q

block null

difference is

H.261 / H.263(3)

the for -

the blocks

position macro

at coefficients

a GOB

difference

macro V plane V each

contains null options

Y plane plane Y + 1 block

other

or the factors

- for be

if of

within

Q

block coefficient

Y U Y

( = all may

more (=

code

of (

vector : fixed

blocks blocks (GOB) = 33 = 33 (GOB) macro

Compression blocks vector pixel

with the

special

to a moving

coefficient coefficients coding coding macro blocks :

is

a

block = 4 moving of

AC DC DCT

is

Video Video for the otherwise there for • • • • • there between apply quantization block = 8 x 8 macro group

      

Interframe Intraframe Intraframe Structures

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof. 

 

15

1 - MPEG (1) MPEG

-

Video Compression Compression Video

1.5 Mbit/s for video 1.5 Mbit/s for for audio Kbit/s 448 Today the first standard is often called MPEG called standard is often first Today the algorithms Compression mediacompressed storing or transmitting Formats for • • • • • decoder is limited The resulting bitrate Includes Video and Audio coding the thanencoder is complex more the , Asymmetric Definition Definition of MPEG = Moving Group Pictures Expert MPEG =     

Properties International standard of ISO 1993 of ISO standard International

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.

 

16

MPEG (2) MPEG

-

interlaced -

Video Compression Compression Video

16:9 for HDTV (Europe and USA) 16:9 for HDTV (Europe 1:1 PAL or NTSC Hz for interlaced 25 Hz or 30 non 50 Hz and 60 Hz for frequency possible lowest Hz is the 23,976 4:3 for PAL 4:3 for • • • • • • Picture frequency Picture frequency Relation of width and height of the pixels to support different TV different pixels support Relation width to of the and height of example: formats; Separation of luminance luminance Separation of and chrominance (similar YUV to using 4:2:0)   

More attributes required than for JPEG for than required More attributes Image preparation Image

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.

 

17

MPEG (3) MPEG Quantization Quantization scaling

- -

frame). The order of pictures -

using the same DCT

Layer

Video Compression Compression Video chrominance chrominance plane) One block compressed using DCT A set of set A block of 16x16 A pixel build of four blocks8x8 of the luminance plane and blocks chrominanceof two 8x8 of the planes (one block of each Contains Contains one picture A set of pictures where of pictures one set at least (usually is encoded first) the A without references to other pictures (I within layer this may be different the from presentation order Controls buffering of video data; each sequence with the starts and amount of memory required for the following sequence

Block Layer Block    Picture Layer Layer Picture  Layer Slice Group of Pictures Layer PicturesGroup of   Sequence Layer Layer Sequence

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof. 6. 5. 4. 3.

2. 1.

18 - run

quantized, quantized,

MPEG (4) MPEG

- encoded

huffman Video Compression Compression Video

references to frame #1 in frame #2 and frame #3 Moving are vectors references to a 16x16 pixel area in prior or following frames describing temporal correlations Parts of frame Parts #1 which change only slightly, be may encoded as

 

Temporal correlations between video frames are used to frames video Temporal correlations between macro reduce the of 16x16 pixelblocks size reduced transformed block is Each 8x8 using the DCT, length encoded, and During image preparation preparation image During the chrominanceis precision

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof. 3.

2. 1.

19

MPEG (5) MPEG

-

Video Compression Compression Video "good" "good" encoders find "good" matches in prior or following frames "medium" encoders find some matches in other frames "bad" encoders do not even try to find moving vectors • • • Usually Usually luminance only the values are similar used to find areas two adjacent macro blocks often have similar moving vectors MPEG does not define MPEG an for finding such a vector Applying Applying the DCT + quantization + difference to the special only. A value is used to describe a complete 8x8 empty block similar area Calculate the difference actual of the 16x16 pixel and the similar area (using luminance and chrominance planes) The moving The moving vector, describing the frame and the position of the      

MPEG defines MPEG how to describe a moving vector only similar 16x16 area in 16x16 area If such other frames. similar an area has been found the block is encoded macro by: While encoding encoding While block a macro the encoder for seeks a

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.

 

20

Frames) are Frames) -

MPEG (6) MPEG Frames)

- -

Frames -

Frames: -

Frames) - , and B and , - , P , -

Video Compression Compression Video frames of the "future" (B "future" the of frames frames that depend only depend (P on preceding frames that frames simplifycalculationB the used to of "past" and the of depend on framestemporal correlations may full frames are transmitted periodically periodically transmitted are (I full frames   

Sequence of I Sequence Several frame types with different temporal temporal different frame Several with types correlations:

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.

 

- 21

MPEG (7) MPEG

-

frames may be encoded like macro blocks of I be encoded like blocksmay of macro frames -

Video Compression Compression Video

Macro blocks of P Macro blocks of only the difference that used, so may be or moving vectors frames be encoded must frame a prior to coding ~ JPEG coding ~ frames Coding I with relation prior P or to Coding without relation to other images Coding other without relation to 8 pixel Apply entropy DCT quantization blocks spectral 8 x + + to frames - frames     -

P I

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.

 

22

MPEG (8) MPEG

-

frames may be encoded be like blocks may of macro frames - Video Compression Compression Video

frames or may be described as an interpolation of I or P frame P frame or I interpolation described as an may be of or frames - P coded be to block macro the to differences its blocks and macro Coding following with relation prior and and P frames to I B of Macro blocks

frames -

 

B

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof. 

23

MPEG (9) MPEG

- frames are used frames -

Video Compression Compression Video

used to support fast forward fast support used to necessary periodic when not I contain low frequency information only, i.e. the DC only the DC coefficient contain low only, i.e. frequency information

frames -

   D

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof. 

24

I B 12 13

B B 11 12

B B 10 11

I 13 B 10 MPEG (10) MPEG

9 B 8 P -

8 B 7 B

7 B 6 B

6 P 9 B

5 B 4 P

4 B 3 B

2 B 3 B

5 B 2 P order

1 I 1 I Video CompressionVideo structure - bitstream display order

 

GOP

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof. 

25

2 (1) 2 1 - - frames enables the enables frames -

MPEG 1 for high quality quality high 1 for

- -

frames and (optionally) D (optionally) frames and -

Video Compression Compression Video 2 defines scaling capabilities, i.e. a decoder a decoder i.e. capabilities, scaling 2 defines 2 is an extension to MPEG to extension an 2 is - - playback with different frame rates with different playback Each picture is coded in different sizes, whereby the coding of size n the coding of sizes, whereby in different Each picture is coded of size n to the image the differences contains only I of placing Adequate

• • Rate; the number of frames per second may be defined by the be defined second may per frames of number Rate; the receiver Spatial; the horizontal horizontal Spatial; theand vertical be adapted by resolution can receiver the Profiles are defined for application application Profiles classesfor are defined profile qualities per levels of Different

   

can select the required scale select required can the MPEG video is flexible standard The MPEG

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof. 

 

26

2 (2) 2 - MPEG

-

Video Compression Compression Video Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.

27

use

, as objects

:

of :

video such

including

4 (1) 4 , )

- types example

scene

these objects

analog a conditions

range data

of

decoder

of with

MPEG quality the specific animation

bitrate -

describe

by as

service

high

face 1993 1993

wide number 4

well - the , i.e. i.e. ,

a very

audio as

very to

data a

(MPEG synthesized

started for

spaces objects be

rebuilding bitrates

represent

D to data -

of

bodies digitized 3

low

audio Compression of video plane video + plane

and - D

- music

very 3 : speech

standard

instead graphics efficiently

dynamic

and a 2D for

faces

and from to

of and the Video Video

flexibility

full

Generic human http://www.cs.ualberta.ca/~anup/MPEG4/Demo.html Speech support Text Video Music • • • • • the instead requires Motivation: Motivation:

 

Work on on Work requirements

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof. 

28

use

-

4 (2) 4 -

MPEG

-

Video Compression Compression Video requirements:

Provide a delivery media that is independent from representation Provide independent is a delivery from thatmedia delivery different borders of the crosstransparently to format environments Provide hyperlinkinginteraction and capabilities intellectualon audiovisual property Manage and protect content only have access authorized users that and algorithms, so Compose Compose audio and visual as well natural and syntheticas audiovisual objects one into scene scenein the Describe the events the objects and mobile ones thus scene, in the various objects the represent Independently allowing their manipulation independent and re accessfor Provide encoding the in the layer resilience residual for to errors channel difficultconditions and for such as types various data

      

Further

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof. 

29

visual -

Coding Coding audio of

--

4 Standards OverviewStandards 4 (3) - 11:2005 Part 11: Scene description and application engine 13:2004 Part 13: Intellectual Property Management and 14:2003 Part 14: MP4 15:2004 Part 15: (AVC) file format 1:2004 Part 1 Systems (first Version published: 1998) 2:2004 Part 2: Visual 3:2001 Part 3: Audio 6:2000 Part 6: Multimedia Delivery Integration Framework 8:2004 Part 8: Carriage of ISO/IEC 14496 contents over IP 10:2005 Part 10: Advanced Video Coding ------MPEG

total of 78 standards subdivided to 22 Parts ISO/IEC 14496 Protection (IPMP) extensions ISO/IEC 14496 ISO/IEC 14496 networks ISO/IEC 14496 ISO/IEC 14496 ISO/IEC 14496 ISO/IEC 14496 (DMIF) ISO/IEC 14496 ISO/IEC 14496 ISO/IEC 14496

          

objects ISO/IEC 14496: Information technology technology Information 14496: ISO/IEC

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof. 

30

4 (4) 4 - MPEG

-

Video Compression Compression Video Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.

31

4 (4) 4 - , e.g. , wavelet e.g. MPEG

CoDec -

Video Compression Compression Video

for textures each each AVO is encoded Each AVO by a special A scene is described is described A scene and tree an object by coordinates for

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.

 

32

VOPs -

matchings

of the first row or

2) 8x8or blocks -

2 using I, P, and B or an alpha channel -

coeffizients 4 Visual -

unvisible (0,0) and 4 Part2: Visual 4 Part2:

4 Visual 4 - - An overview

-

koeffizient rectangles, which consists of - MPEG : DC

are that use MPEG codecs that are

predicition

may be predicted by adjacent blocks (only upper or left block)

Xvid colum 4 Natural Video Video Coding 4 Natural a texture defining a bit mask which pixels are visible/ - • • Motion vectors use half pixel resolution to improve precision of Coefficient first compensation Motion compensation may use 16x16 blocks (as MPEG still textures still textures can be encoded using changing textures are encoded to similarly MPEG encoding of bitmasks: arithmetic encoding (specialized variant) plus motion VOPs may be used to encode foreground and background objects separately A VOP is an arbitrary 2D        

MPEG DivX and Some additional features of MPEG Some additional of features A video scene is made up of video sceneA video object planes of made up is (VOP)

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.

 

 

33

4 - 4 (5) 4 - 1 or 2) in most cases 2) in most 1 or

- MPEG

- 4 is based on VRML on based 4 is -

of a scene adds complexity to the encoder and decoder complexitythe a scene adds to of

Video Compression Compression Video 4 face animation animation 4 face example: - Distinction background and between foregroundwill a lead to MPEG to (comparedcompression better Modelling extensions to the standard are described by the "MPEG bydescribed the are standard the extensions to Description Syntactic Language" (MSDL) new compression techniques data types

    

http://www.cs.ualberta.ca/~anup/MPEG4/Demo.html MPEG Compression efficiency: Compression The scene description of MPEG of scene description The The standard is very flexible, it may be extended by may be extended it flexible, is very standard The

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.    

34 2 -

discs)

ray - matchings blu

4 AVC 4 -

length and ), improve efficiency improve coding), arithmetic and length -

codecs MPEG filters (reduce artifacts, so far a common post processing step) are already taken already are step) processing post a common sofar artifacts, (reduce filters

high quality video (AVC is a onmandatoryvideo is codecfor HDTVvideohigh (AVC quality enable very low video (e.g. enablelow bandwidthvideo very for video conference) • • Flexible macro block ordering, enables arbitrary ordering of macro blocks, could be used to usedbe couldblocks, of macro ordering arbitrary enables ordering, block macroFlexible often) more regions important (update stream video of the robustness enhance (run encoding entropy adaptiveContext Motion vectors use quarter pixel resolution to improve precision of precision improveto resolutionpixel quarter use vectors Motion boundaries pictureof outside reference may vectors Motion Deblocking mandatory becomethus and compensation motion during account into The motion compensation may reference to multiple previous or following pictures (MPEG pictures following or previous multiple to reference may compensation motion The is picturesof order reference and displaythe Thus only). picture one to references allowsonly decoupled. pictures) fadingof efficiencies (higher compensation motionby prediction Weighted pixel4x4 to down 16x16 betweenvary may blocksize Macro a design goal was to be very scalablevery be to was goal a design

        

rates but requires much more CPU resources CPU resources more than but requires much rates video previous MPEG The high The degree of flexibility enables high compression AVC is a very flexible a very flexible AVC is format Advanced Advanced Codec Video is identical (AVC) to H.264

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof. 

 

35 x -

MPEG

-

Video CompressionVideo

7 Overview 7 -

)automatic search capabilities, filtering and selection of - 21: 7: - - includes: includes: financial services, directory services, content providers, aggregators, consumer regulatory devices, services, technology services, delivery services,... MPEG Multimedia framework contents automatic processing, intelligent applications call for proposals in October 1998 efficient efficient identification of multimedia content due to standardized description (semi activities that focusactivities on the development of a multimedia content description interface development of compact descriptions information of         

MPEG MPEG

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.

 

36

MPEG Overview MPEG "Multimedia Framework" has

- 21 -

MPEG

7 Overview 7

-

21: 2: 4: 7: 1: Video Compression Compression Video - - - - - includes: includes: financial services, directory services, content providers, aggregators, consumer devices, regulatory services, technology services, delivery services,... Work on Work on the new standard started in June 2000; the standard for description and search of audio and visual content. MPEG the standard the standard which such products as Digital boxes set top are based and on; DVD the standard for multimedia for the fixed and ; the standard the standard on which products such as Video CD and MP3 are based;       

MPEG MPEG MPEG MPEG MPEG

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.

    

37

uses a nonlinear uses a nonlinear

Companding (Compressing (Compressing Expanding),

: more precise samples low ear requires at

5.10. Audio Compression (1) Compression Audio 5.10. sound compression like silence sound compression methods,

lossy amplitudes amplitudes. than high sample per of number the reduce to formula were silence (as samples of zero), since some people since some people were silencehave less samples of zero), (as sensitive hearing Companding Silence they as if compression: some small treated samples are  

better quality better Some Some compression and taking advantage perception of our can get of sound; Conventional, Conventional, such methods, as Run Length Coding, sound can be used file, to depend results but the heavily the specific sound on

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.

 

38

μ=255

Law - based, to encode digitized based, to audio -

Law and A and Law bit input sample x, normalizing it to , it is it normalizing , bit input sample to x, it - - 1,+1], G.711 standard recommends standard G.711 1,+1], µ - Law: encoder Law: - Since encoder performs are complex, in practice the an approximation produce simpler calculations that much

within interval [ the Experiments indicate that low indicateExperiments speech signals thatamplitudes of amplitudes high than information contain more receivingEncoder 14 International standard, standard, International ISDN digitalfor samples servicestelephony

Law and A and Law

-    

µ

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof. 

39

bit among bits 5 through 5 through 12 bit bits among -

> Segment Code > Segment -

5 = 0 0 1 1 -

bits quantization code is set of the four bits following the bit the set of the code is four following bits bits quantization bit bit is #9 - - 656 Audio Compression Compression Audio (2) – Format

Q0: the 4 S0: subtracting 5 from 5 from S0: subtracting that position -

-

: 5 = 4 in binary representation S2 S1 S0 = 1 0 0 S0 S2 S1 representation 5 = 4 in binary

- Codeword 656| + 33 = 656| - the most significant 1 most significant the 9 Q3 Q28 Q1 Q0 = bits at position

Encode Q3 Encode step 2 in determined position | Adding 33 to the absolute value of the input sample input of the value to absolute the 33 Adding 1 of the most significant the bit position Determining of the input S2 Encode Law - 2. 3. 4.

4. 1. 1. 2. 3.

Example, Example, encode : Algorithm

µ Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.   

40

33 = 655 33 =

655 – -

Audio Compression Compression Audio (3) equals decimal 4, so 43 x 2^4 = 688 = 2^4 equals so 43 x decimal 4,

Law: decoder decoder Law: example - - Decrement the result by 33: 688 result by 33: Decrement the sign: the Use bit P to determine Binary 0101 equals decimal 5, so 5 x 2 + 33 = 43 33 = 2 + Binary 0101 equals so 5 x decimal 5, code: segment power of the the to raised Multiply result by 2 the Binary 100 Multiply quantization 33: and add the code by 2 Law Law and A - 3. 4. 2. 1.

µ

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.

41 1; up to 1; up -

3 3 3 - - - 1, from 32 to from 32 to 1, - 2, Layer 2, -

2 and Layer 2

- 3) -

1, Layer 1, - 3) - channel (stereo) coding coding of channel (stereo) -

2, and from 32 to 320 Kbit/s for Layer Kbit/s and from 32 to 320 2, - MPEG Audio (1)Audio MPEG

channel and two (mono) 1, and from 8 to 160 Kbit/s for Layer for Kbit/s160 8 to from and 1, - - 2 BC: (1994, ISO/IEC 13818 2 BC: (1994, ISO/IEC 1: (1992, ISO/IEC 11172 ISO/IEC 1: (1992, - - Predefined bit rates range from 32 to 448 Kbit/s for layer Kbit/s for to 448 from 32 rates range bit Predefined for Layer 384 Kbit/s • Lower extension, bit rates down from 32 to 256 Kbit/s for 256 Kbit/s 32 to down from extension, bit rates Lower bit rate Layer channels) coded be can 22.05, extension,16, sampling Low samplefrequencies rateat and 24 kHz A backwards compatible multichannel MPEG extension to 5 main channels enhancement" channel plus a low (5.1 frequent 3 coding methods are defined: Layer defined: are coding methods 3 signal digitized sound signal and 48 kHz sampling rate 44.1, high 32, quality audio atused for      

MPEG MPEG

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.

 

42

3) -

MPEG Audio (2)Audio MPEG

7) - 1 audio decoder based coding - - 4: (1999, ISO/IEC 14496 4: (1999, ISO/IEC 2 AAC (): (1997, (1997, Coding): (Advanced 2 AAC Audio - - Object sampling rates of 8 to 96 kHz 96 8 to of sampling rates an by interpreted and read be cannot compatible, backward Not MPEG A high quality audio coding standard for 1 to 48 channels channels 48 at A high 1 to quality audio coding standard for   

MPEG MPEG 13818 ISO/IEC

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.

 

43

Kbit/s

128 Kbit/s 256 (DCC) - - Broadcast Application 112 Audio Internet 192

DVD Digital audio 384 Kbit/s, Stereo 384 Kbit/s, Digital compact Cassette

2 BC three are layers three 2 BC - Delay Layer 19 to 50 ms

35 to 100 ms 59 to 150 ms

4:1 ratio 1 and MPEG 1 and 6:1 to 8:1 6:1 to - 10:1 to 12:1 10:1 to Compression

3 1 2 - - -

(MP3) Layer Layer Layer

complexity, performance delay increase and with each performance complexity, layer Both in MPEG in Both defined. coding These Layers represent family a of algorithms. but codec Basic model is the same,

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof. 

44

Psychoacoustic Psychoacoustic (1)

Critical low audible at high wide band: narrow frequencies, at frequencies Range is about 20 Hz to 20 kHz, most sensitive at 2 to 4 kHz to 2 sensitive at most 20 kHz, Hz toRange 20 is about  

Spectral Spectral masking effect the psychoacoustic psychoacoustic the principles. psychoacoustic term The describes human the characteristic auditory of the system human Sensitivity hearing of MPEG's modern perceptual perceptual audio coding modern techniques exploit MPEG's

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.   

45 can be up to 100 to up can be

postmasking , the the , ms

Psychoacoustic Psychoacoustic (2)

ms Masking effect before and after a strong sound a strong and after before effectMasking 5 to Pre masking 2 is about

 

Temporal Temporal masking effect

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof. 

46

* 32) and 1152 *

subban subband

of frequency (the are audio samples

MPEG Audio encoderAudio MPEG 1 (12 samples/ 2/3 (36 * 32) - - subbands Mask Ratio) for each Mask Ratio) - to - samples are packaged containing into frames 384

The input audio stream through simultaneouslypassesa threshold the masking model that determines psychoacoustic (SMR, Signal subband Layer samples in Layer samples in The input audio stream passes bank that divides through a filter the inputinto 32 transformed from time domain to frequency domain). The

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.

 

47

2

-

data Ancillary 1 Layer1 -

1 frame 1 - Layer

Samples

are written in the frame in the are written

could by represented be 384)

- Bitstreams (0 Scalefactors 1 this allocation 15 1 this can be 0 to - subband

are scaled such that the largest one one largest the such that scaled are

Audio: Audio: subbands 256) - Bit rate, and coding and coding mode rate, - Allocation (128 2/3 (36 * 32) in each frame (36 * 2/3 subband -

CRC (0,16)

(samples in (samples different

subband

FrameFormat MPEG of (32) Header

SCFSI (scale factor selection information) has 2 bits, it indicates indicates it selection bits, SCFSI 2 information) has (scale factor per scale3 factors 2 or whether 1, has 6 bits has 6 1152 samples in Layer each resembles a Layer is divided parts,A frame into 3 different numbers of bits), for Layer for bits), numbers of different bits per each signals of 12 The scaleeach factor than one, greater not one but close to becomes very number of channels, the bit channels, number of in sample each Bit allocation per bits of number describes the subband The header of each frame contains general contains suchinformation as the frame of each The header the sampling the synchronizationfrequency, MPEG layer, information,

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.    

 

48

3 -

" Layer

Samples

main_data_begin

Bitstreams information (136,256) Audio: Audio: Side Side

CRC (0,16)

3 variable allowed is rate bit

- 32 Header Encoder can borrow bits donated from past frames from donated can borrow bitsEncoder Side information includes " bits point, a 9 Frame Format MPEG of

 

For Layer For

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof. 

49

should should

subband subband

Bit Allocation (1) Allocation Bit Since sample rate, samples per frame and bit rate are known, theare known, and bit rate per frame samples Since sample rate, is available fixed bits per frame

be allocated no more bits than necessary to make the the to make necessary bits than be allocated no more quantization noise inaudible For the most efficient compression, the most efficient each For below the masking threshold, while using than not more the available bits over a frame. The bit allocation algorithm works in this way, that the the that bit allocation way, in this The works algorithm quantization noise (difference between the original spectral and values the quantized spectral values) is The psychoacoustic psychoacoustic The model and allocation the bit algorithm are invoked to determine allocated the number of bits to the quantization each scaled sample of in each

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof. 

 

50

> -

2: - Bit Allocation (2) Allocation Bit

3: 1 Layer and - -

Outer iteration loop Outer Achieving quantization a smaller noise larger number requires a bits of If the number of bits exceeds the number of bits available number of bits exceeds the number of the If leading larger quantization to The process is done by two nested iteration loops two nested is done byThe process The quantized Coding Hoffman value are coded by loop) iteration loop (rate Inner The process repeats until no more code bits can be allocated bits can be no more code until repeats The process        

For Layer For Layer For

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.

 

51

3 (high - 4 - uniform quantization, -

1 -

rates - Advanced Advanced Coding) Audio

AAC : ( AAC

2 -

2 AAC is the state the art of is the schemeaudio coding for 2 AAC - 3 and usesin a lot of details coding tools for new - Digital Digital system Audio via Internet

MPEG  

The only coding used within MPEG audio scheme the standard Application improved low bit at quality on the contrary standards onlyAAC the format of the encoded audio data. frequency resolution filter bank, non filter bank, resolution frequency coding,Huffman loop structure), iteration but improves on Layer generic codinggeneric up it givessignals; multichannel of stereo to MPEG backwards compatibility coding paradigm the same basicfollowsas Layer AAC MPEG

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof. 

 

 

52

e.g. BMP, TIFF, TIFF, e.g. BMP, PNG JPEG, e.g. SVG MP3 e.g. WAV, e.g. MIDI in practice not relevant AVI, e.g.

raster image vector image wave audio synthesis audio 5.11. MultimediaFormats File

combined formats/ container formats formats/ container combined audio video images Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.

53

8 bit per channel - rare deployment on non Windows platforms well not for the suited Internet 1 resulting 24 in 1, 4, 8, bit none (mostly) RLE (only colorat 4 or 8 bit depth supported) on Windows platform: standard format large files        

Color depth: Color Compression: Advantages: Disadvantages:    

,

File Formats: Formats: File BMP

BitMaP

grayscale

1 or 3 color channels no alpha channels only Windows color management Monochrome, RGB; indexed colors      Microsoft Corp. () .bmp

Channels: ICC profiles: Development: Color representation: File extension: File extension: Name:

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.

 

 

 

54

)

PackBits

16 bit per channel - files are comparatively large, thus not well suited for Internet use different compression methods cause interoperability issues 1 None RLE ( Group LZW, CCITT 3 and 4 JPEG multiple pictures per file are supported extendable platform independent          

Color depth: Color Compression: Advantages: Disadvantages:    

; RGB; File Formats:File TIFF

grayscale

) Image File Format ) Image File

ged 1, 3, 4 color channels or channels alpha 20 indexed colors indexed others and monochrome; monochrome; CMYK Systems, Systems, Inc.), Microsoft, HP, as scanner as and printer other well manufacturers

, . tif     yes  Aldus Corporation (now part part of Adobe (now Corporation Aldus Tag( .

Channels: ICC profiles: ICC Color representation: Development: File extension: File Name: Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.      

55

)

compression not suited

16 bit per channel - lossy for graphics (unsatisfying results with outlines, missing transparency) no advanced features (see JPEG2000 1 lossless (prediction, Huffman; used seldom: verynot effective) DCT well suited colorful for images widely supported good compression results         Color depth: Color Compression: Advantages: Disadvantages:    

File Formats: Formats: File JPG

; RGB; CMYK ; RGB;

3 or 4 color channels no alpha channels and others grayscale Group (JPEG) File Group (JPEG) Interchange Format (JFIF)    yes JPEG, ISO JPEG,  .jpg, .jpg, . Joint Photographic Expert

Channels: ICC profiles: Color representation: File extension: Development: Name:

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.      

56

and lossless

more processing needed compared to JPEG still not widely supported Wavelet better compression results at same quality compared to artifacts)(no JPEG errors images in file affect only locally (Region ROI of Interest) many options for progressive image display possible         Disadvantages: Compression: Advantages:   

File Formats:File JPEG2000

yes

; RGB; CMYK ; RGB;

16 bit per channel -

1 256 grayscale and others JPEG, ISO JPEG, Group 2000     .jp2  Joint Photographic Expert

Color depth: Color ICC profiles: Channels: Color representation: Development: File extension: Name:

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.

      

57

not suited for colorful images (only 256 colors, limited to lossless compression) two incompatible versions (GIF87a und GIF89a) LZW well suited for Internet graphics widely supported interlaced: progressive image display possible animated graphics possible license issues until mid 2004         Compression: Advantages: Disadvantages:

  

File Formats:File GIF

max. 8 bit 1 transparent color possible indexed indexed colors

    no CompuServe CompuServe Inc. Graphics Interchange Format .

Color depth: Color Channels: ICC profiles: Development: Color representation: File extension: Name:

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.

    

 

58

web

web

since IE4 (no since IE4

16 bit per channel 16 bit - Improved interlacing Improved Still lacking by support browsers 1 LZ77) todeflate (similar Supported by browsers Netscape transparency!), 4.04 GIF Superset of functionality       Disadvantages: Color depth: Color Compression: Advantages:    

File Formats:File PNG

; RGB

3 channels 1 alpha channel grayscale indexed colors Technology Technology (MIT)

png   limited   Massachusetts Massachusetts of Institute Portable Portable Network Graphics .

ICC profiles: Channels: Color representation: Development: File extension: Name:

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.

 

 

 

59

files are files comparatively large, suited for Internet thus not use PICT (Macs), TIFF PICT Metafile (WMF; Windows), EPSI none (usually) JPEG well suited printing for supports vector graphics and raster graphics        Disadvantages: Format of Preview Images: of Format Preview Compression: Advantages:    

;

File Formats:File EPS

grayscale

8 bit per channel -

1 1, 3, or 4 color channels no alpha channels monochrome; CMYK RGB; and others eps    yes   Adobe Inc. Adobe Systems, Encapsulated Encapsulated PostScript .

Color depth: ICC profiles: Channels: Development: Color representation: File extension: Name:

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.

 

 

 

60

1.1)

Format

1 Layer 1 1,2 Layer 1 3 4 - - - Audio FormatAudio (Java

Sun MPEG MPEG MPEG Format Microsoft Wave Interleaved Video Audio Microsoft ogg (not an acronym) QuicktimeApple Audio/Video Formats Audio/Video

Suffix MooV .

,

mov . .au .avi .ogg .mp4 . .mp2 . Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.

61

cost,

, bit colors 16 only

bitrate

Microsoft AVI for large uniform uniform for areas large Microsoft, good quality, fast computation, fast high computation, quality, Microsoft, good cost computational high TV quality, high quality, good colors, high computational cost computational high colors, good quality, high computational much for movement, high , without good pictures bad bit colors 8 fast, only relatively lossless, Encoding, Length Random codec creates about 60 MB/min for 384x288 pixels and 25 MB/min for about 60 codec creates

1 5.10 codec creates about 40 MB/min for 384x288 pixels and 25 MB/min for about 40 5.10 codec creates -

Indeo RLE 1 Video MPEG

Indeo fps. Cinepak fps.

Some of the codecs used for video compression in an AVI file: AVI in an video compression for codecs used the of Some RIFF is Resource and serves as general as general File isRIFF serves Interchange Resource and Format was defined exchanging It multimedia for data types. format purpose Electronic Arts. from IFF IBM based on and by Microsoft followed with a header RIFF starts and lists. by chunks AVI Files AVI Files special RIFF files. are a case of

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.

   

62

1) available as on -

Microsoft WMV

4 Video - 9) -

Ray discs -

Blue Three versions: WMV1, WMV2, WMV3 (released WMV3 (released with WMV2, versions: Three WMV1, Media Player 7 WMV3 (also called VC High definition High definition available format (WMVHD) Supports DRM files Similar to MPEG Window Window Media Video Proprietary video from Microsoft codec encapsulated Often ASF (Advanced in Streaming Format)

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.

       

63 -

4. -

based based compression of -

based based measurement data. Quicktime -

4 is based on the QuickTime 4 is based QuickTime on the -

Apple Apple

feel user. for the -

Apple claimsMPEG that with MPEG 6 works QuickTime video format. the video compression the video compression algorithms all are from Apple and not documented. It is possible is possible add new compression It to algorithms and driver codecs. for video Unfortunately, the technical details are hidden. Especially QuickTime comes with a lot of convenient convenient comes QuickTime a lot of with to functions ease programmer's the a standard and create look task and video and synchronized audio. can also be used time for It QuickTime is a method is a method QuickTime time for

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof. 

    

64

2 with -

1 with 352x288 1 with 352x288 - 2 with 720x576 pixels -

384 Kbit/s audio. 35 to 60 min384 audio. fit on a Kbit/s -

Storing Multimedia Data Multimedia Storing

6144 Kbit/s audio. 60 to 180 min fit on a to 180 min fit audio. 60 6144 Kbit/s -

including 64 including (4.7GB). DVD single disc MB). single (650 (DVD) uses MPEG The digital video disc interlaced frames. and allowsThere to 9.8 is up Mbit/s data The super video compact disc (SVCD) uses MPEG The super video(SVCD) uses compact disc interlaced frames. allows There 480x576 pixels to 2.6 and is up 64 includingMbit/s data single CD (650 MB). According to the standard, isthere 1.15 standard, to the MB). According CD (650 single kHz samplingaudio with 44.1 audio and 224 Mbit/sKbit/s video rate. popular formats: VCD, SVCD, and DVD. and formats:SVCD, popular VCD, MPEG (VCD) uses The video compact disc and can store pixelsup to 74 min and audio on a of video For multimediastoring home, at data there currentlyare three

Prof. Dr. Paul Müller, University of Kaiserslauternof University Müller, Paul Dr. Prof.

 

 

kl.de -

2263

-

67653 Kaiserslautern 67653 - Email: [email protected] Email: Phone: +49(0) 631 205 631 +49(0) Phone: D Integrated Communication Systems ICSY Systems Communication Integrated Kaiserslautern of University Science Computer of Department 3049 Box P.O. Prof. Dr. Paul Müller