SlideShare ist ein Scribd-Unternehmen logo
1 von 22
Issues involved in Multimedia
        handling online

  TODAY, MULTIMEDIA IS NO LONGER A
 DREAM, BUT A REALITY , ALTHOUGH THE
     TECHNOLOGY IS YET TO REACH ITS
              MATURITY.
 IT HAS BECOME POSSIBLE TO OVERCOME
   SOME CHALLENGES , BUT STILL MANY
    CHALLENGES REMAIN TO BE SOLVED
           SATISFACTORILY.
The issues involved with handling
  multimedia online arelisted below:


I. Bandwidth limitations of communication
     channels.
II. Real-time processing requirements.
III. Inter-media synchronization.
IV. Inter-media continuity.
V. End-to-end delays and delay jitters.
VI. Multimedia indexing and retrieval.
I . Bandwidth limitations

 Limited bandwidth of communication channels poses the
    most serious challenge in multimedia communication.
   Some of the media streams, such as video sequences, large-
    sized still images, even stereo quality audio requires large
    volumes of data to be transmitted in a sort-time, considering
    real-time requirements.
   Suppose, we want to transmit a color image of 1024 x 768
    picture elements (called pixels) through a telephone channel,
    supported with modem, having speed of 14.4 Kbps.
   Assuming 24-bits for each pixel, i.e., 8-bits for each color
    component ( Red, Green, Blue) , the total number of bits to be
    transmitted for the entire image is given by
   Total number of bits, B = 1024 x 768 x 24 = 18.8 x 106
Bandwidth limitations ( continue . . )

 Therefore, total time required to transmit this image is
  18.8 x 106 , i.e., approx. 22 minutes, which is excessively
  high.
 The total time will be halved, if we double the modem
  speed, but 11 minutes of transmission time is still too
  high.
 Let us now consider the example of a video conferencing.
  We consider a fairly small frame size of 352 x 288 pixels
  and a colored video sequence having 24-bits /pixel,
  acquired at a frame rate of 30 frames per second, which
  is to be transmitted through a leased line of bandwidth
  384 Kbits/second.
Bandwidth limitations ( continue . . )

 From given data, the raw video bit rate is ( 352 x 288
  x 24 x 30), i.e., 72.9 Mbits/second.
 Hence, we cannot transmit the video through the
  given channel bandwidth, unless the data is
  significantly compressed.
 The actual situation is not as bad as we may conclude
  from the above discussions.
Bandwidth limitations ( continue . . )




 We can observe that most of the pixels have almost
  the same intensity as those of the neighbors.
 Only at the boundaries of the object, the intensities
  change significantly.
Bandwidth limitations ( continue . . )

 Thus, there is considerable redundancy present in the
  images, since the pixels are spatially correlated to a
  great extent.
 If this redundancy could be exploited, significant data
  compression can be achieved.
 In the case of video sequence, the amount of data to be
  handled is much more than those involved with still
  images, since the video sequence in the link below to
  carefully observe the redundancies.
 We can observe that the redundancies are not present
  only within a frame ( Spatial Redundancy), but also
  between successive frames ( Temporal Redundancy).
Bandwidth limitations ( continue . . )
Bandwidth limitations ( continue . . )

 We can see that the successive frames are very
  similar to each other, it is because of the fact that
  between successive frame time, only a limited
  movement of the moving objects is possible and if
  the back ground is stationary, then most of the
  pixels do not exhibit any change at all between
  successive frames.
 In the above video sequence, we can only see lip
  movements and eye movements between
  successive frames.
 Thus, although the data to be handled is much
  more in the video, there is a scope to exploit both
  spatial and temporal redundancy.
Bandwidth limitations ( continue . . )

 We are definitely convinced that data compression is
  an essential requirement for images and video.
 In the case of CD-quality stereo audio sample at 44.1
  KHz, the raw data rate is 192 Kbps, which is also
  some what high, if we consider leased line bandwidth
  or wireless channel bandwidth. Hence, audio
  compression is also a requirement.
 Other media streams ( text, graphics, animation etc)
  have relatively less data contents in most of the
  applications and may not require compression.
Bandwidth limitations ( continue . . )


 However , we should not think that we can perform
  data compression techniques that achieve
  significant compression are irreversible.
 These therefore lead to loss of data and quality
  degradation.
 There is always a trade-off that is present between
  compression, i.e., bandwidth reduction and
  quality.
II . Real-time processing requirements

 Whichever technique we may adopt to exploit the
  redundancies and achieve data compression,
  significant amount of processing will be involved.
 If the processing time is high, the advantage of data
  compression may be lost.
 In our still image example, if we are able to achieve a
  compression of 20:1, the entire image can be
  transmitted in a minute.
 If however, the processing time to achieve this
  compression had been in the order of minutes, the
  advantage of compression would be lost.
II . Real-time processing requirements (continue . . .)

 Challenges are much more in the case of video.
 Video frames are captured at a rate of 30 frames per
  second and this leaves a time of 33 milliseconds between
  successive frames.
 Hence, video compression and whatever additional
  processing are required, need to completed within one
  frame time.
 Although, today’s processors, operating at GHz rate are
  extraordinarily fast, quite often even such high speed
  processors are unable to perform real-time capability is a
  highly challenging and a topic of research.
III . Inter-media sychronysation


 The media streams available from different and
  independent sources and are asynchronous with
  respect to each other.
 Lack of lip-synchronization is a commonly
  observed problem in multi-media systems
  involving audio and video.
 Lack of synchronization between the different
  media may even defeat the purpose of multimedia
  presentation.
Inter-media sychronysation ( continue . .)

 Multimedia standards have addressed this problem
  and adopted “time-stamping” to ensure
  synchronization.
 Time-stamps, with respect to a system clock
  reference ( SCR) are appended with the different
  media ( audio,
 Video etc) packets before integrating the individual
  streams into a multimedia one.
 At the receiver end, the individual media streams
  are decoded and presented to the play back units in
  accordance with the time-stamps obtained from
  the pack and packet headers.
IV . Inter-media continuity

 The extent of data compression with acceptable
    reconstruction quality is highly data-dependent.
   Wherever redundancy is more high compression
    ratios are achievable, but redundancy may vary.
   Take the example of a video sequence.
   Each frame will undergo different extent of
    compression and in turn will vary the bit rate from
    one frame to other.
   If we use a channel that supports constant bit rate,
    accommodating a variable bit rate source will be a
    challenging task.
Inter-media continuity ( continue . . .)

 This is achieved by providing a buffer before the bit-
  stream generation.
 The buffer may be filled up at variable rate, but
  emptied during transmission at a constant rate.
 One must therefore ensure that at no instant should
  the buffer be completely emptied and the channel
  starves for data( known as buffer underflow
  problem).
 On the other hand, at no instant should the buffer be
  completely filled up and further incoming data is lost
  (known as buffer over flow problem)
Inter-media continuity ( continue . . .)

 In both these extreme situations of buffer overflow
  and underflow, the continuity is lost during
  presentation.
 The extent we can tolerate such discontinuities
  depends upon the medium under consideration.
 If it a video and you occasionally lose a frame, your
  eyes may not even notice that, whereas any
  discontinuity in the audio stream will be
  immediately detected by your ears.
Inter-media continuity ( continue . . .)

 It is because our ears are more sensitive than our
  eyes as the ultimate detector.
 We can say that it is easy to fool our eyes, but it is not
  easy to fool our ears.
 However , it must not be misunderstood that intra-
  media discontinuity can happen only due to under
  flow/overflow problems.
 It may happen because of inadequate processing
  speed, packet loss, channel errors and many other
  conditions.
V . End-to-end delays and delay jitters

 This is yet another important consideration, which
  we had mentioned in above sections.
 In multimedia broadcast or conferencing, if the user
  receive the multimedia contents after considerable
  delays or different users receive the same contents at
  different times, the interactivity is lost.
 The multimedia standards available till date have
  addressed this problem and specified what is
  acceptable.
VI . Multimedia indexing and retrieval

 As the price of digital storage media decreases, the
  storage capacity increases and multimedia
  applications gain more popularity, there is a
  requirement to store large number of multimedia
  files.
 Unless these files are properly indexed, retrieval of
  desired multimedia file becomes a tough task, in
  view of the search complexities.
 If the multimedia files are based on their contents
  and then a content-base query system is developed,
  efficient retrieval can be obtained.
Multimedia indexing and retrieval ( continue . . )

 Often, for quick browsing of multimedia files, video
  summaries are needed and automated generation of
  video summaries is a very challenging task.
 All these issues are being addressed in the upcoming
  MPEG-7 multimedia standards.

Weitere ähnliche Inhalte

Andere mochten auch

Voice over IP: Issues and Protocols
Voice over IP: Issues and ProtocolsVoice over IP: Issues and Protocols
Voice over IP: Issues and Protocols
Videoguy
 
1991 SYNCHRONIZATION OF MULTIMEDIA OBJECTS
1991 SYNCHRONIZATION OF MULTIMEDIA OBJECTS1991 SYNCHRONIZATION OF MULTIMEDIA OBJECTS
1991 SYNCHRONIZATION OF MULTIMEDIA OBJECTS
Personal Interactor
 
Copyright and ethics in relation to multimedia
Copyright and ethics in relation to multimedia Copyright and ethics in relation to multimedia
Copyright and ethics in relation to multimedia
Jayatunga Amaraweera
 

Andere mochten auch (17)

Multimedia technology for websites
Multimedia technology for websitesMultimedia technology for websites
Multimedia technology for websites
 
MAT Chapter 1
MAT Chapter 1MAT Chapter 1
MAT Chapter 1
 
Voice over IP: Issues and Protocols
Voice over IP: Issues and ProtocolsVoice over IP: Issues and Protocols
Voice over IP: Issues and Protocols
 
13584 27 multimedia mining
13584 27 multimedia mining13584 27 multimedia mining
13584 27 multimedia mining
 
Ch4
Ch4Ch4
Ch4
 
Textgraphics1
Textgraphics1Textgraphics1
Textgraphics1
 
1991 SYNCHRONIZATION OF MULTIMEDIA OBJECTS
1991 SYNCHRONIZATION OF MULTIMEDIA OBJECTS1991 SYNCHRONIZATION OF MULTIMEDIA OBJECTS
1991 SYNCHRONIZATION OF MULTIMEDIA OBJECTS
 
Ch08
Ch08Ch08
Ch08
 
Multi media Data mining
Multi media Data miningMulti media Data mining
Multi media Data mining
 
Multimedia
MultimediaMultimedia
Multimedia
 
Copyright and ethics in relation to multimedia
Copyright and ethics in relation to multimedia Copyright and ethics in relation to multimedia
Copyright and ethics in relation to multimedia
 
5) multimedia notes
5) multimedia notes5) multimedia notes
5) multimedia notes
 
Computer graphics
Computer graphicsComputer graphics
Computer graphics
 
Multimedia Issues and Problems
Multimedia Issues and ProblemsMultimedia Issues and Problems
Multimedia Issues and Problems
 
Multimedia data mining using deep learning
Multimedia data mining using deep learningMultimedia data mining using deep learning
Multimedia data mining using deep learning
 
Msd ch2 issues in multimedia
Msd ch2 issues in multimediaMsd ch2 issues in multimedia
Msd ch2 issues in multimedia
 
grapics and multimedia
grapics and multimediagrapics and multimedia
grapics and multimedia
 

Ähnlich wie Issue in handling multimedia online

Download presentation source
Download presentation sourceDownload presentation source
Download presentation source
Videoguy
 
Ltfs new-archive-workflow-whitepaper
Ltfs new-archive-workflow-whitepaperLtfs new-archive-workflow-whitepaper
Ltfs new-archive-workflow-whitepaper
Marc Bourhis
 
Video Conferencing, The Enterprise and You
Video Conferencing, The Enterprise and YouVideo Conferencing, The Enterprise and You
Video Conferencing, The Enterprise and You
Videoguy
 
Image and Video Compression Techniques In Image Processing an Overview
Image and Video Compression Techniques In Image Processing an OverviewImage and Video Compression Techniques In Image Processing an Overview
Image and Video Compression Techniques In Image Processing an Overview
MangaiK4
 

Ähnlich wie Issue in handling multimedia online (20)

Download presentation source
Download presentation sourceDownload presentation source
Download presentation source
 
Multi media networking
Multi media networking Multi media networking
Multi media networking
 
M.sc.iii sem digital image processing unit v
M.sc.iii sem digital image processing unit vM.sc.iii sem digital image processing unit v
M.sc.iii sem digital image processing unit v
 
Digital video
Digital videoDigital video
Digital video
 
05999528
0599952805999528
05999528
 
05 presentation
05 presentation05 presentation
05 presentation
 
Video Streaming Compression for Wireless Multimedia Sensor Networks
Video Streaming Compression for Wireless Multimedia Sensor NetworksVideo Streaming Compression for Wireless Multimedia Sensor Networks
Video Streaming Compression for Wireless Multimedia Sensor Networks
 
Video Compression
Video CompressionVideo Compression
Video Compression
 
A VIDEO COMPRESSION TECHNIQUE UTILIZING SPATIO-TEMPORAL LOWER COEFFICIENTS
A VIDEO COMPRESSION TECHNIQUE UTILIZING SPATIO-TEMPORAL LOWER COEFFICIENTSA VIDEO COMPRESSION TECHNIQUE UTILIZING SPATIO-TEMPORAL LOWER COEFFICIENTS
A VIDEO COMPRESSION TECHNIQUE UTILIZING SPATIO-TEMPORAL LOWER COEFFICIENTS
 
Ltfs new-archive-workflow-whitepaper
Ltfs new-archive-workflow-whitepaperLtfs new-archive-workflow-whitepaper
Ltfs new-archive-workflow-whitepaper
 
Chapter 1-Introduction to Media-Past, Present and Future.ppt
Chapter 1-Introduction to Media-Past, Present and Future.pptChapter 1-Introduction to Media-Past, Present and Future.ppt
Chapter 1-Introduction to Media-Past, Present and Future.ppt
 
video comparison
video comparison video comparison
video comparison
 
Dr.U.Priya, Head & Assistant Professor of Commerce, Bon Secours for Women, Th...
Dr.U.Priya, Head & Assistant Professor of Commerce, Bon Secours for Women, Th...Dr.U.Priya, Head & Assistant Professor of Commerce, Bon Secours for Women, Th...
Dr.U.Priya, Head & Assistant Professor of Commerce, Bon Secours for Women, Th...
 
International Journal of Computational Engineering Research(IJCER)
 International Journal of Computational Engineering Research(IJCER)  International Journal of Computational Engineering Research(IJCER)
International Journal of Computational Engineering Research(IJCER)
 
Video Conferencing, The Enterprise and You
Video Conferencing, The Enterprise and YouVideo Conferencing, The Enterprise and You
Video Conferencing, The Enterprise and You
 
report
reportreport
report
 
Ijcatr04051003
Ijcatr04051003Ijcatr04051003
Ijcatr04051003
 
Image and Video Compression Techniques
Image and Video Compression Techniques Image and Video Compression Techniques
Image and Video Compression Techniques
 
Image and Video Compression Techniques In Image Processing an Overview
Image and Video Compression Techniques In Image Processing an OverviewImage and Video Compression Techniques In Image Processing an Overview
Image and Video Compression Techniques In Image Processing an Overview
 
New coding techniques, standardisation, and quality metrics
New coding techniques, standardisation, and quality metricsNew coding techniques, standardisation, and quality metrics
New coding techniques, standardisation, and quality metrics
 

Kürzlich hochgeladen

Activity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfActivity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdf
ciinovamais
 
Seal of Good Local Governance (SGLG) 2024Final.pptx
Seal of Good Local Governance (SGLG) 2024Final.pptxSeal of Good Local Governance (SGLG) 2024Final.pptx
Seal of Good Local Governance (SGLG) 2024Final.pptx
negromaestrong
 
1029-Danh muc Sach Giao Khoa khoi 6.pdf
1029-Danh muc Sach Giao Khoa khoi  6.pdf1029-Danh muc Sach Giao Khoa khoi  6.pdf
1029-Danh muc Sach Giao Khoa khoi 6.pdf
QucHHunhnh
 

Kürzlich hochgeladen (20)

Activity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfActivity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdf
 
Micro-Scholarship, What it is, How can it help me.pdf
Micro-Scholarship, What it is, How can it help me.pdfMicro-Scholarship, What it is, How can it help me.pdf
Micro-Scholarship, What it is, How can it help me.pdf
 
psychiatric nursing HISTORY COLLECTION .docx
psychiatric  nursing HISTORY  COLLECTION  .docxpsychiatric  nursing HISTORY  COLLECTION  .docx
psychiatric nursing HISTORY COLLECTION .docx
 
Spatium Project Simulation student brief
Spatium Project Simulation student briefSpatium Project Simulation student brief
Spatium Project Simulation student brief
 
Unit-IV; Professional Sales Representative (PSR).pptx
Unit-IV; Professional Sales Representative (PSR).pptxUnit-IV; Professional Sales Representative (PSR).pptx
Unit-IV; Professional Sales Representative (PSR).pptx
 
ICT Role in 21st Century Education & its Challenges.pptx
ICT Role in 21st Century Education & its Challenges.pptxICT Role in 21st Century Education & its Challenges.pptx
ICT Role in 21st Century Education & its Challenges.pptx
 
Seal of Good Local Governance (SGLG) 2024Final.pptx
Seal of Good Local Governance (SGLG) 2024Final.pptxSeal of Good Local Governance (SGLG) 2024Final.pptx
Seal of Good Local Governance (SGLG) 2024Final.pptx
 
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
 
Mixin Classes in Odoo 17 How to Extend Models Using Mixin Classes
Mixin Classes in Odoo 17  How to Extend Models Using Mixin ClassesMixin Classes in Odoo 17  How to Extend Models Using Mixin Classes
Mixin Classes in Odoo 17 How to Extend Models Using Mixin Classes
 
Magic bus Group work1and 2 (Team 3).pptx
Magic bus Group work1and 2 (Team 3).pptxMagic bus Group work1and 2 (Team 3).pptx
Magic bus Group work1and 2 (Team 3).pptx
 
SOC 101 Demonstration of Learning Presentation
SOC 101 Demonstration of Learning PresentationSOC 101 Demonstration of Learning Presentation
SOC 101 Demonstration of Learning Presentation
 
On National Teacher Day, meet the 2024-25 Kenan Fellows
On National Teacher Day, meet the 2024-25 Kenan FellowsOn National Teacher Day, meet the 2024-25 Kenan Fellows
On National Teacher Day, meet the 2024-25 Kenan Fellows
 
1029-Danh muc Sach Giao Khoa khoi 6.pdf
1029-Danh muc Sach Giao Khoa khoi  6.pdf1029-Danh muc Sach Giao Khoa khoi  6.pdf
1029-Danh muc Sach Giao Khoa khoi 6.pdf
 
Introduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsIntroduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The Basics
 
Basic Civil Engineering first year Notes- Chapter 4 Building.pptx
Basic Civil Engineering first year Notes- Chapter 4 Building.pptxBasic Civil Engineering first year Notes- Chapter 4 Building.pptx
Basic Civil Engineering first year Notes- Chapter 4 Building.pptx
 
How to Manage Global Discount in Odoo 17 POS
How to Manage Global Discount in Odoo 17 POSHow to Manage Global Discount in Odoo 17 POS
How to Manage Global Discount in Odoo 17 POS
 
Holdier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfHoldier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdf
 
Understanding Accommodations and Modifications
Understanding  Accommodations and ModificationsUnderstanding  Accommodations and Modifications
Understanding Accommodations and Modifications
 
2024-NATIONAL-LEARNING-CAMP-AND-OTHER.pptx
2024-NATIONAL-LEARNING-CAMP-AND-OTHER.pptx2024-NATIONAL-LEARNING-CAMP-AND-OTHER.pptx
2024-NATIONAL-LEARNING-CAMP-AND-OTHER.pptx
 
Python Notes for mca i year students osmania university.docx
Python Notes for mca i year students osmania university.docxPython Notes for mca i year students osmania university.docx
Python Notes for mca i year students osmania university.docx
 

Issue in handling multimedia online

  • 1. Issues involved in Multimedia handling online TODAY, MULTIMEDIA IS NO LONGER A DREAM, BUT A REALITY , ALTHOUGH THE TECHNOLOGY IS YET TO REACH ITS MATURITY. IT HAS BECOME POSSIBLE TO OVERCOME SOME CHALLENGES , BUT STILL MANY CHALLENGES REMAIN TO BE SOLVED SATISFACTORILY.
  • 2. The issues involved with handling multimedia online arelisted below: I. Bandwidth limitations of communication channels. II. Real-time processing requirements. III. Inter-media synchronization. IV. Inter-media continuity. V. End-to-end delays and delay jitters. VI. Multimedia indexing and retrieval.
  • 3. I . Bandwidth limitations  Limited bandwidth of communication channels poses the most serious challenge in multimedia communication.  Some of the media streams, such as video sequences, large- sized still images, even stereo quality audio requires large volumes of data to be transmitted in a sort-time, considering real-time requirements.  Suppose, we want to transmit a color image of 1024 x 768 picture elements (called pixels) through a telephone channel, supported with modem, having speed of 14.4 Kbps.  Assuming 24-bits for each pixel, i.e., 8-bits for each color component ( Red, Green, Blue) , the total number of bits to be transmitted for the entire image is given by  Total number of bits, B = 1024 x 768 x 24 = 18.8 x 106
  • 4. Bandwidth limitations ( continue . . )  Therefore, total time required to transmit this image is 18.8 x 106 , i.e., approx. 22 minutes, which is excessively high.  The total time will be halved, if we double the modem speed, but 11 minutes of transmission time is still too high.  Let us now consider the example of a video conferencing. We consider a fairly small frame size of 352 x 288 pixels and a colored video sequence having 24-bits /pixel, acquired at a frame rate of 30 frames per second, which is to be transmitted through a leased line of bandwidth 384 Kbits/second.
  • 5. Bandwidth limitations ( continue . . )  From given data, the raw video bit rate is ( 352 x 288 x 24 x 30), i.e., 72.9 Mbits/second.  Hence, we cannot transmit the video through the given channel bandwidth, unless the data is significantly compressed.  The actual situation is not as bad as we may conclude from the above discussions.
  • 6. Bandwidth limitations ( continue . . )  We can observe that most of the pixels have almost the same intensity as those of the neighbors.  Only at the boundaries of the object, the intensities change significantly.
  • 7. Bandwidth limitations ( continue . . )  Thus, there is considerable redundancy present in the images, since the pixels are spatially correlated to a great extent.  If this redundancy could be exploited, significant data compression can be achieved.  In the case of video sequence, the amount of data to be handled is much more than those involved with still images, since the video sequence in the link below to carefully observe the redundancies.  We can observe that the redundancies are not present only within a frame ( Spatial Redundancy), but also between successive frames ( Temporal Redundancy).
  • 8. Bandwidth limitations ( continue . . )
  • 9. Bandwidth limitations ( continue . . )  We can see that the successive frames are very similar to each other, it is because of the fact that between successive frame time, only a limited movement of the moving objects is possible and if the back ground is stationary, then most of the pixels do not exhibit any change at all between successive frames.  In the above video sequence, we can only see lip movements and eye movements between successive frames.  Thus, although the data to be handled is much more in the video, there is a scope to exploit both spatial and temporal redundancy.
  • 10. Bandwidth limitations ( continue . . )  We are definitely convinced that data compression is an essential requirement for images and video.  In the case of CD-quality stereo audio sample at 44.1 KHz, the raw data rate is 192 Kbps, which is also some what high, if we consider leased line bandwidth or wireless channel bandwidth. Hence, audio compression is also a requirement.  Other media streams ( text, graphics, animation etc) have relatively less data contents in most of the applications and may not require compression.
  • 11. Bandwidth limitations ( continue . . )  However , we should not think that we can perform data compression techniques that achieve significant compression are irreversible.  These therefore lead to loss of data and quality degradation.  There is always a trade-off that is present between compression, i.e., bandwidth reduction and quality.
  • 12. II . Real-time processing requirements  Whichever technique we may adopt to exploit the redundancies and achieve data compression, significant amount of processing will be involved.  If the processing time is high, the advantage of data compression may be lost.  In our still image example, if we are able to achieve a compression of 20:1, the entire image can be transmitted in a minute.  If however, the processing time to achieve this compression had been in the order of minutes, the advantage of compression would be lost.
  • 13. II . Real-time processing requirements (continue . . .)  Challenges are much more in the case of video.  Video frames are captured at a rate of 30 frames per second and this leaves a time of 33 milliseconds between successive frames.  Hence, video compression and whatever additional processing are required, need to completed within one frame time.  Although, today’s processors, operating at GHz rate are extraordinarily fast, quite often even such high speed processors are unable to perform real-time capability is a highly challenging and a topic of research.
  • 14. III . Inter-media sychronysation  The media streams available from different and independent sources and are asynchronous with respect to each other.  Lack of lip-synchronization is a commonly observed problem in multi-media systems involving audio and video.  Lack of synchronization between the different media may even defeat the purpose of multimedia presentation.
  • 15. Inter-media sychronysation ( continue . .)  Multimedia standards have addressed this problem and adopted “time-stamping” to ensure synchronization.  Time-stamps, with respect to a system clock reference ( SCR) are appended with the different media ( audio,  Video etc) packets before integrating the individual streams into a multimedia one.  At the receiver end, the individual media streams are decoded and presented to the play back units in accordance with the time-stamps obtained from the pack and packet headers.
  • 16. IV . Inter-media continuity  The extent of data compression with acceptable reconstruction quality is highly data-dependent.  Wherever redundancy is more high compression ratios are achievable, but redundancy may vary.  Take the example of a video sequence.  Each frame will undergo different extent of compression and in turn will vary the bit rate from one frame to other.  If we use a channel that supports constant bit rate, accommodating a variable bit rate source will be a challenging task.
  • 17. Inter-media continuity ( continue . . .)  This is achieved by providing a buffer before the bit- stream generation.  The buffer may be filled up at variable rate, but emptied during transmission at a constant rate.  One must therefore ensure that at no instant should the buffer be completely emptied and the channel starves for data( known as buffer underflow problem).  On the other hand, at no instant should the buffer be completely filled up and further incoming data is lost (known as buffer over flow problem)
  • 18. Inter-media continuity ( continue . . .)  In both these extreme situations of buffer overflow and underflow, the continuity is lost during presentation.  The extent we can tolerate such discontinuities depends upon the medium under consideration.  If it a video and you occasionally lose a frame, your eyes may not even notice that, whereas any discontinuity in the audio stream will be immediately detected by your ears.
  • 19. Inter-media continuity ( continue . . .)  It is because our ears are more sensitive than our eyes as the ultimate detector.  We can say that it is easy to fool our eyes, but it is not easy to fool our ears.  However , it must not be misunderstood that intra- media discontinuity can happen only due to under flow/overflow problems.  It may happen because of inadequate processing speed, packet loss, channel errors and many other conditions.
  • 20. V . End-to-end delays and delay jitters  This is yet another important consideration, which we had mentioned in above sections.  In multimedia broadcast or conferencing, if the user receive the multimedia contents after considerable delays or different users receive the same contents at different times, the interactivity is lost.  The multimedia standards available till date have addressed this problem and specified what is acceptable.
  • 21. VI . Multimedia indexing and retrieval  As the price of digital storage media decreases, the storage capacity increases and multimedia applications gain more popularity, there is a requirement to store large number of multimedia files.  Unless these files are properly indexed, retrieval of desired multimedia file becomes a tough task, in view of the search complexities.  If the multimedia files are based on their contents and then a content-base query system is developed, efficient retrieval can be obtained.
  • 22. Multimedia indexing and retrieval ( continue . . )  Often, for quick browsing of multimedia files, video summaries are needed and automated generation of video summaries is a very challenging task.  All these issues are being addressed in the upcoming MPEG-7 multimedia standards.