Perspectives in distributed source coding

Size: px
Start display at page:

Download "Perspectives in distributed source coding"

Transcription

1 UC Berkeley Perspectives in distributed source coding Kannan Ramchandran UC Berkeley

2 Media transmission today High-end video camera Mobile device Challenges Low-power video sensor Back-end server Aerial surveillance vehicles High compression efficiency High resilience to transmission errors Fleible encoder/decoder compleity distribution Low latency How to meet these requirements simultaneously?

3 Today s video codec systems Driven by downlink model: High compression efficiency Rigid compleity distribution Comple transmitter, light receiver Prone to transmission error Decoding relies deterministically on one predictor Motion Compensated Prediction Error +

4 Rethink video codec architecture? Alternatives to rigid compleity partition, deterministic prediction-based framework? Interesting tool: distributed source coding

5 Roadmap Introduction and motivation Distributed source coding: foundations & intuition Application landscape Distributed source coding for video applications: Encryption & Compression Video transmission: foundations and architecture Low-encoder-compleity High-compression efficiency + Robustness Multi-camera scenario

6 Motivation: sensor networks Y Consider correlated nodes X, Y X Dense, low-power sensor-networks Communication between X and Y epensive. Can we eploit correlation without communicating? Assume Y is compressed independently. How to compress X close to H(X Y)? Key idea: discount I(X;Y). H(X Y) = H(X) I(X;Y)

7 Distributed source coding: Slepian-Wolf 73 R y H(Y) H(Y X) A ACHIEVABLE RATE-REGION C B Separate encoding of X and Y X Y H(X Y) H(X) R

8 Distributed source coding Source coding with side information: (Slepian-Wolf, 73, Wyner-Ziv, 76) X Encoder Decoder Y X^ X and Y are correlated sources. Y is available only to decoder. Lossless coding (S-W): no loss of performance over when Y is available at both ends if the statistical correlation between X and Y is known. Lossy coding (W-Z): for Gaussian statistics, no loss of performance over when Y known at both ends. Constructive solutions: (Pradhan & Ramchandran (DISCUS) DCC 99, Garcia-Frias & Zhao Comm. Letters 01, Aaron & Girod DCC 02, Liveris, Xiong & Georghiades DCC '03, ) Employs statistical instead of deterministic mindset.

9 Eample: geometric illustration Source Signal to decoder Assume signal and noise are Gaussian, iid

10 Eample: geometric illustration Source Side information Assume signal and noise are Gaussian, iid

11 3 cosets Eample: scalar Wyner-Ziv N X Y X + Y X^ Q Partition 3 X^ X Y Q Encoder: send the inde of the coset (log 2 3 bits) Decoder: decode X based on Y and signaled coset

12 Application Landscape

13 Sensor networks M-channel Multiple Description coding Media broadcast Media security: Data-hiding, watermarking, steganography Fundamental duality between source coding and channel coding with side-information Compression of encrypted data Video transmission

14 Duality bet. source & channel coding with side-info Source coding with side information X Decoder Encoder m m Xˆ Sensor networks, video-over-wireless, multiple description, secure compression S Channel coding with side information (CCSI) m Encoder X Y mˆ Channel Decoder S Watermarking, audio data hiding, interference pre-cancellation, multi-antenna wireless broadcast. Pradhan, Chou and Ramchandran, Trans. on IT, May 2003

15 Compressing encrypted content without the cryptographic key

16 Secure multimedia for home networks Uncompressed encrypted video (HDCP protocol) Can increase wireless range with lower data rate But how to compress encrypted video without access to crytpographic key?

17 Application: Compressing Encrypted Data Conventional method: X Source Compress Unconventional method: H(X) bits Cryptograhic Key Encrypt K (H(X) bits) H(X) bits X Encrypt Y H(X) bits Compress Source Cryptograhic Key K (H(X) bits) Johnson & Ramchandran (ICIP 2003), Johnson et. al (Trans. on SP, Oct. 2004)

18 Eample 10,000 bits Compressed 5,000 bits Original Image Encrypted Image Encrypted Image Decoding compressed Image Final Reconstructed Image

19 Application: compressing encrypted data 10,000 bits 5,000 bits? Source Image Encrypted Image Decoded Image Source X Key Insight! Joint Decoder/Decrypter Y U Encrypter Encoder Decoder Decrypter Syndrome Reconstructed Source Xˆ Key K K Key

20 Overview Content provider Encryption X Y=X+K End user K ISP Compression S Joint Decoder Y = X + K where X is indep. of K Slepian-Wolf theorem: can send X at rate H(Y K) = H(X) Security is not compromised! K X Johnson, Ishwar, Prabhakaran & Ramchandran (Trans. on SP, Oct. 2004)

21 Practical Code Constructions Use a linear transformation (hash/bin) Design cosets to have maimal spacing State of the art linear codes (LDPC codes) Fied length to fied length compression Source Codewords Bin 1 Bin 2 Bin 3

22 Framework: Encryption Encryption: Stream cipher X 1 Source X 2 X 3 X n y i i k Graphical model captures eact encryption relationship i Y 1 Y 2 Y 3 Y n Compression K 1 K 2 K 3 K n S 1 S 2 S m

23 Source Models IID Model X 1 X 2 X 3 X n 1-D Markov Model X 1 X 2 X 3 X n 2-D Markov Model X i-1,j-1 X i-1,j X i,j-1 X i,j

24 Encrypted image compression results piel image (10,000 bits) No compression possible with IID model 1-D Markov Source Model Source Image Encrypted Image Compressed Bits Decoded Image 2-D Markov Source Model

25 Schonberg,Yeo, Draper & Ramchandran, DCC 07 Compression of encrypted video Video offers both temporal and spatial prediction Decoder has access to unencrypted prior frames Blind approach (encoder has no access to key) Foreman Saves 33.00% Garden Saves 17.64% Football Saves 7.17%

26 Encrypted video compression results Show rate savings percentage Rate used (output bits/source bit) is shown for reference Compare to operation on unencrypted video JPEG-LS lossless intra encoding of frames Leading lossless video codec eploits temporal redundancy JPEG-LS (unencrypted video) Foreman 50.96% R= Garden 26.80% R= Football 33.00% R= Leading lossless video codec (unencrypted video) 58.87% R= % R= % R= Proposed approach (encrypted video, encoder has no access to key) 33.00% R= % R= % R=0.9283

27 Distributed source coding for video transmission: overview

28 When is DSC useful in video transmission? Uncertainty in the side information Low compleity encoding Transmission packet drops Multicast & scalable video coding Fleible decoding Physically distributed sources Multi-camera setups

29 Low compleity encoding Motivation current frame Low- Compleity Encoder DSC Encoder Low-compleity (no motion search) Trans-coding proy High- Compleity Decoder High- Compleity Encoder DSC Decoder Side-info Generator reference frame Low- Compleity Decoder current frame High-compleity (interpolated or compensated motion) (Puri & Ramchandran, Allerton 02, Aaron, Zhang & Girod, Asilomar 02)

30 Transmission packet loss current frame current frame DSC encoder DSC Decoder corrupted reference frame Recover current frame with (corrupted) reference frame that is not available at the encoder Distributed source coding: can help if statistical correlation bet. current and corrupted ref. frames known at the encoder

31 Standards compatibility X = Frame n X = Frame n DSC Encoder MPEG Encoder DSC Decoder MPEG Decoder X = corrupted Frame n Y = Frame n-1 Y = Corrupted Frame n-1 Can be made compatible with standards-based codecs Corrupted current frame is side-info at DSC decoder (Aaron, Rane, Rebollo-Monedero & Girod 04, 05, Sehgal, Jagmohan & Ahuja: 04, Wang, Majumdar & Ramchandran: 04, 05)

32 Multicast & scalable video coding Enhancement layer at Rate R Base layer at Rate R Multicast Accommodate heterogeneous users Different channel conditions Different video qualities (spatial, temporal, PSNR) Majumdar & Ramchandran, 04 Tagliasacchi, Majumdar & Ramchandran, 04 Sehgal, Jagmohan & Ahuja, PCS 04 Wang, Cheung & Ortega, EURASIP 06 Xu & Xiong, 06

33 Fleible decoding {Y 1, Y 2,, Y N } could be Neighboring frames in time Forward/backward playback without buffering Neighboring frames in space Random access to frame in multi-view setup X Encoder Decoder X ^ Y i {Y 1, Y 2,, Y N } User Control Cheung, Wang & Ortega, VCIP 2006, PCS 2007 Draper & Martinian, ISIT 2007

34 Multi-camera setups Dense placement of low-end video sensors Sophisticated back-end processing 3-D view reconstruction Object tracking Super-resolution Multi-view coding and transmission Back-end server

35 Important enabler Rate-efficient camera calibration Visual correspondence determination Tosic & Frossard, EUSIPCO 2007 Yeo, Ahammad & Ramchandran, VCIP 2008 Scene

36 DSC for video transmission: PRISM- I targeting low-compleity encoding

37 MCPC: a closer look n Z n Y T X Previous decoded blocks (inside the search range) Y 1 Y T Y M Motion-compensated prediction Y T Motion T Prediction error (DFD) Z Current block X

38 Motion-free encoding? X Y 1 Y M Y MCPC Encoder 1 log M n R(D) Motion T?? Quantized? + (1/n)log MDFD MCPC Decoder Y M X MSE =? The encoder does not have or cannot use Y 1,, Y M and The decoder does not know T. The encoder may work at rate: R(D) + (1/n )log M bits per piel. How to decode and what is the performance?

39 Is a No-Motion Encoder Possible? Candidate Predictor Blocks Let s Cheat! Candidate Predictor Blocks Y 1... Y M MV Y 1 Y T... Y M X Wyner Ziv Encoder Wyner-Ziv coset-inde Wyner Ziv Decoder X Let s cheat & let the decoder have the MV classical W-Z problem The encoder works at same rate as predictive coder

40 Is a No-Motion Encoder Possible? Y 1... Y M Y 1... Y M X Encoder Decoder X Can decoding work without a genie? Yes Can we match the performance of predictive coding? Yes (when DFD statistics are Gaussian) Ishwar, Prabhakaran, and Ramchandran ICIP 03.

41 Motion search at decoder Low-compleity motion-free encoder X Wyner-Ziv Encoder bin inde Y 1 Need mechanism to detect decoding failure In theory: joint typicality (statistical consistency) Wyner-Ziv Decoder Y T Decoding failure In practice: use CRC Compleity knob to share search compleity between enc. & decoder bin inde Need concept of motion compensation at decoder Wyner-Ziv Decoder Y M Wyner-Ziv Decoder X Decoding failure

42 Practical implementation Y 1... Y M X Encoder Channel Y 1 Y M... Decoder ^ X Can be realized through decoder motion search Etendable to when side-information is corrupted robustness to channel loss Correlation between X and Y i difficult to estimate due to low-compleity encoding compression efficiency compromised

43 Robustness Results: PRISM-I video codec Qualcomm s channel simulator for CDMA X wireless networks Stefan (SIF, 2.2 Mbps, 5% error) PRISM vs. H.263+ FEC

44 DSC for video transmission: PRISM II targeting highcompression efficiency & robustness

45 Cause of compression inefficiency Recall X Encoder Decoder Y X^ Y N + X Challenge: correlation estimation, i.e. finding H(X Y) = H(N) N = Video innovation + Effect of channel + Quantization noise Hard to model without motion search Without accurate estimate of the total noise statistics, need to over-design compression inefficiency. What if compleity were less of a constraint and we allow motion search at the encoder?

46 Video innovation can be accurately modeled When there are no channel errors: N = Video innovation + Quantization noise DSC vs. H.263+ DSC vs. H.264 Foreman Sequence (QCIF, 15 fps) Milani, Wang & Ramchandran, VCIP 2007

47 Modeling effect of channel at encoder X = Frame n X = Frame n DSC Encoder DSC Decoder Y = corrupted Frame n-1 Goal: estimate H (X Y )

48 Finding H(X Y ) Philosophy: have control over uncertainty set at decoder e.g. orchestrate decoder designs for Y if Y is available Y = Z if Y is not available Eample: Z mv 2 Y mv 1 X Frame t-2 Frame t-1 Frame t Encoder has access to both Y and Z Natural temporal redundancy in video: diversity gain an intact predictor in Frame t-2 (Z) is typically a better predictor than a corrupted predictor Y in Frame t-1 J. Wang, V. Prabhakaran & K. Ramchandran: ICIP 06

49 Finding H(X Y ) Z mv 2 Y mv 1 X Frame t-2 Frame t-1 Frame t If we have some knowledge about the channel: Y = Y if Y is intact Z if Y is corrupted with probability (1-p) with probability p We obtain H(X Y, decoder state) = (1-p)*H(X Y) + p*h(x Z)

50 Another way to think about it Z mv 2 Y mv 1 X Frame t-2 Frame t-1 Frame t H(X Y, decoder state) = (1-p)*H(X Y) + p*h(x Z) = p*[h(x Z) H(X Y)] + H(X Y) Effect of channel Video innovation

51 Yet another way to think about it Z mv 2 Y mv 1 X Frame t-2 Frame t-1 Frame t H(X Y, decoder state) = (1-p)*H(X Y) + p*h(x Z) = p*[h(x Z) H(X Y)] + H(X Y) Can be achieved by applying channel code to sub-bin indices Additional syndrome (sub-bin inde) for drift correction Bare minimum syndrome (bin inde) needed when channel is clean

52 Robustness result Setup: Channel: Simulated Gilbert-Elliot channel with p g = 0.03 and p b = 0.3

53 Robustness result Setup: Channel: Simulated CDMA channel Stefan (SIF) sequence 1 GOP = 20 frames 1 mbps baseline, 1.3 mbps total (15 fps) 7.1% average packet drop rate Football (SIF) sequence 1 GOP = 20 frames 900 kbps baseline, 1.12 mbps total (15 fps) 7.4% average packet drop rate

54 Videos Garden , 1.4 mbps, 15 fps, gop size 15, 4% error (Gilbert Elliot channel with 3% error rate in good state and 30% in bad state) DSC vs. H.263+ FEC Football , 1.12 mbps, 15 fps, gop 15, simulated CDMA channel with 5% error DSC vs. H.263+ FEC

55 DSC for multi-camera video transmission:

56 Distributed multi-view coding Video decoder operates jointly X 1 Encoder 1 Channel ^ X 1 X 2 Encoder 2 Channel ^ X 2 X 3 Encoder 3 Video encoders operate independently Channel Feedback possibly present Joint Decoder X 3 ^

57 Active area of research Distributed multi-view image compression Down-sample + Super-resolution [Wagner, Nowak & Baraniuk, ICIP 2003] Geometry estimation + rendering [Zhu, Aaron & Girod, SSP 2003] Direct coding of scene structure [Gehrig & Dragotti, ICIP 2005] [Tosic & Frossard, ICIP 2007] Unsupervised learning of geometry [Varodayan, Lin, Mavlankar, Flierl & Girod, PCS 2007] Distributed multi-view video compression Geometric constraints on motion vectors in multiple views [Song, Bursalioglu, Roy-Chowdhury & Tuncel, ICASSP 2006] [Yang, Stankovic, Zhao & Xiong, ICIP 2007] Fusion of temporal and inter-view side-information [Ouaret, Dufau & Ebrahimi, VSSN 2006] [Guo, Lu, Wu, Gao & Li, VCIP 2006] MCTF followed by disparity compensation [Flierl & Girod, ICIP 2006] Robust distributed multi-view video compression Disparity search / View synthesis search [Yeo, Wang & Ramchandran, ICIP 2007]

58 Robust distributed multi-view video transmission X 1 Encoder 1 X 2 Encoder 2 Noisy and bandwidth constrained channels Packet Erasure Channel Packet Erasure Channel Video decoder operates jointly to recover video streams ^ X 1 ^ X 2 X 3 Encoder 3 Video encoders operate independently and under compleity and latency constraint. Packet Erasure Channel Joint Decoder X 3 ^

59 Side information from other camera views ^ X = Frame t X = reconstructed Frame t Ideal Encoder f(x) Ideal Decoder How should we look in other camera views? Naïve approach of looking everywhere can be etremely rate-inefficient Possible approaches Y = neighboring Frame t Y = corrupted Frame t-1 View synthesis search Disparity search

60 Epipolar geometry Given an image point in one view, corresponding point in the second view is on the epipolar line X 2 X 3 Upshot: Disparity search is reduced to a 1-D search X l e e C C Camera 1 Camera 2

61 Decoder disparity search Camera 1 Temporal Poor reference Camera 2 Spatial Good reference Disparity Vector Frame t-1 Y DS Frame t X (1) Search along epipolar line X = Y DS + N DS Etension of decoder motion search using epipolar geometry [Yeo & Ramchandran, VCIP 2007]

62 PRISM-DS vs MPEG with FEC Ballroom sequence (from MERL) , 960 Kbps, 30fps, GOP size 25, 8% average packet loss Original MPEG+FEC PRISM-DS Drift is reduced in PRISM-DS [Yeo & Ramchandran, VCIP 2007]

63 Summary and concluding thoughts Overview of distributed source coding Foundations, intuitions and constructions Application landscape DSC for video transmission Compression of encrypted content DVC for single-camera systems: compleity and robustness attributes DVC for multi-camera systems truly distributed application

64 Lots of open challenges Core problems deeply intertwined Side-information generation Correlation modeling and estimation: fundamental tradeoffs between encoding compleity, compression performance and robustness? Optimal co-eistence with eisting standards? Multi-camera systems Distributed correlation estimation among sources Spatial versus temporal correlations when will the correlation among sources dominate correlation within each source? Interplay with wireless networking protocols?

65 THANK YOU!

Wyner-Ziv Coding of Motion Video

Wyner-Ziv Coding of Motion Video Wyner-Ziv Coding of Motion Video Anne Aaron, Rui Zhang, and Bernd Girod Information Systems Laboratory, Department of Electrical Engineering Stanford University, Stanford, CA 94305 {amaaron, rui, bgirod}@stanford.edu

More information

Distributed Video Coding Using LDPC Codes for Wireless Video

Distributed Video Coding Using LDPC Codes for Wireless Video Wireless Sensor Network, 2009, 1, 334-339 doi:10.4236/wsn.2009.14041 Published Online November 2009 (http://www.scirp.org/journal/wsn). Distributed Video Coding Using LDPC Codes for Wireless Video Abstract

More information

WYNER-ZIV VIDEO CODING WITH LOW ENCODER COMPLEXITY

WYNER-ZIV VIDEO CODING WITH LOW ENCODER COMPLEXITY WYNER-ZIV VIDEO CODING WITH LOW ENCODER COMPLEXITY (Invited Paper) Anne Aaron and Bernd Girod Information Systems Laboratory Stanford University, Stanford, CA 94305 {amaaron,bgirod}@stanford.edu Abstract

More information

Free Viewpoint Switching in Multi-view Video Streaming Using. Wyner-Ziv Video Coding

Free Viewpoint Switching in Multi-view Video Streaming Using. Wyner-Ziv Video Coding Free Viewpoint Switching in Multi-view Video Streaming Using Wyner-Ziv Video Coding Xun Guo 1,, Yan Lu 2, Feng Wu 2, Wen Gao 1, 3, Shipeng Li 2 1 School of Computer Sciences, Harbin Institute of Technology,

More information

A Study of Encoding and Decoding Techniques for Syndrome-Based Video Coding

A Study of Encoding and Decoding Techniques for Syndrome-Based Video Coding MITSUBISHI ELECTRIC RESEARCH LABORATORIES http://www.merl.com A Study of Encoding and Decoding Techniques for Syndrome-Based Video Coding Min Wu, Anthony Vetro, Jonathan Yedidia, Huifang Sun, Chang Wen

More information

Systematic Lossy Forward Error Protection for Error-Resilient Digital Video Broadcasting

Systematic Lossy Forward Error Protection for Error-Resilient Digital Video Broadcasting Systematic Lossy Forward Error Protection for Error-Resilient Digital Broadcasting Shantanu Rane, Anne Aaron and Bernd Girod Information Systems Laboratory, Stanford University, Stanford, CA 94305 {srane,amaaron,bgirod}@stanford.edu

More information

CHROMA CODING IN DISTRIBUTED VIDEO CODING

CHROMA CODING IN DISTRIBUTED VIDEO CODING International Journal of Computer Science and Communication Vol. 3, No. 1, January-June 2012, pp. 67-72 CHROMA CODING IN DISTRIBUTED VIDEO CODING Vijay Kumar Kodavalla 1 and P. G. Krishna Mohan 2 1 Semiconductor

More information

Distributed Video Coding

Distributed Video Coding Distributed Video Coding BERND GIROD, FELLOW, IEEE, ANNE MARGOT AARON, SHANTANU RANE, STUDENT MEMBER, IEEE, AND DAVID REBOLLO-MONEDERO Invited Paper Distributed coding is a new paradigm for video compression,

More information

Robust wireless video multicast based on a distributed source coding approach $

Robust wireless video multicast based on a distributed source coding approach $ Signal Processing 86 (2006) 3196 3211 www.elsevier.com/locate/sigpro Robust wireless video multicast based on a distributed source coding approach $ M. Tagliasacchi a,, A. Majumdar b, K. Ramchandran b,

More information

Agrowing percentage of the world population now uses image and

Agrowing percentage of the world population now uses image and [ Christine Guillemot, Fernando Pereira, Luis Torres, Touradj Ebrahimi, Riccardo Leonardi, and Jöern Ostermann ] DIGITAL VISION Distributed Monoview and Multiview Video Coding [Basics, problems, and recent

More information

Systematic Lossy Error Protection based on H.264/AVC Redundant Slices and Flexible Macroblock Ordering

Systematic Lossy Error Protection based on H.264/AVC Redundant Slices and Flexible Macroblock Ordering Systematic Lossy Error Protection based on H.264/AVC Redundant Slices and Flexible Macroblock Ordering Pierpaolo Baccichet, Shantanu Rane, and Bernd Girod Information Systems Lab., Dept. of Electrical

More information

Video Quality Monitoring for Mobile Multicast Peers Using Distributed Source Coding

Video Quality Monitoring for Mobile Multicast Peers Using Distributed Source Coding Quality Monitoring for Mobile Multicast Peers Using Distributed Source Coding Yao-Chung Lin, David Varodayan, and Bernd Girod Information Systems Laboratory Electrical Engineering Department, Stanford

More information

Systematic Lossy Error Protection of Video Signals Shantanu Rane, Member, IEEE, Pierpaolo Baccichet, Member, IEEE, and Bernd Girod, Fellow, IEEE

Systematic Lossy Error Protection of Video Signals Shantanu Rane, Member, IEEE, Pierpaolo Baccichet, Member, IEEE, and Bernd Girod, Fellow, IEEE IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, VOL. 18, NO. 10, OCTOBER 2008 1347 Systematic Lossy Error Protection of Video Signals Shantanu Rane, Member, IEEE, Pierpaolo Baccichet, Member,

More information

MULTI-STATE VIDEO CODING WITH SIDE INFORMATION. Sila Ekmekci Flierl, Thomas Sikora

MULTI-STATE VIDEO CODING WITH SIDE INFORMATION. Sila Ekmekci Flierl, Thomas Sikora MULTI-STATE VIDEO CODING WITH SIDE INFORMATION Sila Ekmekci Flierl, Thomas Sikora Technical University Berlin Institute for Telecommunications D-10587 Berlin / Germany ABSTRACT Multi-State Video Coding

More information

Systematic Lossy Error Protection of Video based on H.264/AVC Redundant Slices

Systematic Lossy Error Protection of Video based on H.264/AVC Redundant Slices Systematic Lossy Error Protection of based on H.264/AVC Redundant Slices Shantanu Rane and Bernd Girod Information Systems Laboratory Stanford University, Stanford, CA 94305. {srane,bgirod}@stanford.edu

More information

Modeling and Optimization of a Systematic Lossy Error Protection System based on H.264/AVC Redundant Slices

Modeling and Optimization of a Systematic Lossy Error Protection System based on H.264/AVC Redundant Slices Modeling and Optimization of a Systematic Lossy Error Protection System based on H.264/AVC Redundant Slices Shantanu Rane, Pierpaolo Baccichet and Bernd Girod Information Systems Laboratory, Department

More information

INFORMATION THEORY INSPIRED VIDEO CODING METHODS : TRUTH IS SOMETIMES BETTER THAN FICTION

INFORMATION THEORY INSPIRED VIDEO CODING METHODS : TRUTH IS SOMETIMES BETTER THAN FICTION INFORMATION THEORY INSPIRED VIDEO CODING METHODS : TRUTH IS SOMETIMES BETTER THAN FICTION Nitin Khanna, Fengqing Zhu, Marc Bosch, Meilin Yang, Mary Comer and Edward J. Delp Video and Image Processing Lab

More information

Dual Frame Video Encoding with Feedback

Dual Frame Video Encoding with Feedback Video Encoding with Feedback Athanasios Leontaris and Pamela C. Cosman Department of Electrical and Computer Engineering University of California, San Diego, La Jolla, CA 92093-0407 Email: pcosman,aleontar

More information

Project Proposal: Sub pixel motion estimation for side information generation in Wyner- Ziv decoder.

Project Proposal: Sub pixel motion estimation for side information generation in Wyner- Ziv decoder. EE 5359 MULTIMEDIA PROCESSING Subrahmanya Maira Venkatrav 1000615952 Project Proposal: Sub pixel motion estimation for side information generation in Wyner- Ziv decoder. Wyner-Ziv(WZ) encoder is a low

More information

Joint Optimization of Source-Channel Video Coding Using the H.264/AVC encoder and FEC Codes. Digital Signal and Image Processing Lab

Joint Optimization of Source-Channel Video Coding Using the H.264/AVC encoder and FEC Codes. Digital Signal and Image Processing Lab Joint Optimization of Source-Channel Video Coding Using the H.264/AVC encoder and FEC Codes Digital Signal and Image Processing Lab Simone Milani Ph.D. student simone.milani@dei.unipd.it, Summer School

More information

MULTIVIEW DISTRIBUTED VIDEO CODING WITH ENCODER DRIVEN FUSION

MULTIVIEW DISTRIBUTED VIDEO CODING WITH ENCODER DRIVEN FUSION MULTIVIEW DISTRIBUTED VIDEO CODING WITH ENCODER DRIVEN FUSION Mourad Ouaret, Frederic Dufaux and Touradj Ebrahimi Institut de Traitement des Signaux Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015

More information

LAYERED WYNER-ZIV VIDEO CODING FOR NOISY CHANNELS. A Thesis QIAN XU

LAYERED WYNER-ZIV VIDEO CODING FOR NOISY CHANNELS. A Thesis QIAN XU LAYERED WYNER-ZIV VIDEO CODING FOR NOISY CHANNELS A Thesis by QIAN XU Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements for the degree of MASTER

More information

Minimax Disappointment Video Broadcasting

Minimax Disappointment Video Broadcasting Minimax Disappointment Video Broadcasting DSP Seminar Spring 2001 Leiming R. Qian and Douglas L. Jones http://www.ifp.uiuc.edu/ lqian Seminar Outline 1. Motivation and Introduction 2. Background Knowledge

More information

Video Transmission. Thomas Wiegand: Digital Image Communication Video Transmission 1. Transmission of Hybrid Coded Video. Channel Encoder.

Video Transmission. Thomas Wiegand: Digital Image Communication Video Transmission 1. Transmission of Hybrid Coded Video. Channel Encoder. Video Transmission Transmission of Hybrid Coded Video Error Control Channel Motion-compensated Video Coding Error Mitigation Scalable Approaches Intra Coding Distortion-Distortion Functions Feedback-based

More information

Exploring the Distributed Video Coding in a Quality Assessment Context

Exploring the Distributed Video Coding in a Quality Assessment Context Exploring the Distributed Video Coding in a Quality Assessment Context A. Banitalebi *, H. R. Tohidypour Digital Multimedia Lab, ECE Dept., University of British Columbia Abstract In the popular video

More information

Interleaved Source Coding (ISC) for Predictive Video Coded Frames over the Internet

Interleaved Source Coding (ISC) for Predictive Video Coded Frames over the Internet Interleaved Source Coding (ISC) for Predictive Video Coded Frames over the Internet Jin Young Lee 1,2 1 Broadband Convergence Networking Division ETRI Daejeon, 35-35 Korea jinlee@etri.re.kr Abstract Unreliable

More information

COMP 249 Advanced Distributed Systems Multimedia Networking. Video Compression Standards

COMP 249 Advanced Distributed Systems Multimedia Networking. Video Compression Standards COMP 9 Advanced Distributed Systems Multimedia Networking Video Compression Standards Kevin Jeffay Department of Computer Science University of North Carolina at Chapel Hill jeffay@cs.unc.edu September,

More information

Video Over Mobile Networks

Video Over Mobile Networks Video Over Mobile Networks Professor Mohammed Ghanbari Department of Electronic systems Engineering University of Essex United Kingdom June 2005, Zadar, Croatia (Slides prepared by M. Mahdi Ghandi) INTRODUCTION

More information

Research Topic. Error Concealment Techniques in H.264/AVC for Wireless Video Transmission in Mobile Networks

Research Topic. Error Concealment Techniques in H.264/AVC for Wireless Video Transmission in Mobile Networks Research Topic Error Concealment Techniques in H.264/AVC for Wireless Video Transmission in Mobile Networks July 22 nd 2008 Vineeth Shetty Kolkeri EE Graduate,UTA 1 Outline 2. Introduction 3. Error control

More information

Analysis of Video Transmission over Lossy Channels

Analysis of Video Transmission over Lossy Channels 1012 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 18, NO. 6, JUNE 2000 Analysis of Video Transmission over Lossy Channels Klaus Stuhlmüller, Niko Färber, Member, IEEE, Michael Link, and Bernd

More information

Parameters optimization for a scalable multiple description coding scheme based on spatial subsampling

Parameters optimization for a scalable multiple description coding scheme based on spatial subsampling Parameters optimization for a scalable multiple description coding scheme based on spatial subsampling ABSTRACT Marco Folli and Lorenzo Favalli Universitá degli studi di Pavia Via Ferrata 1 100 Pavia,

More information

Adaptive Distributed Compressed Video Sensing

Adaptive Distributed Compressed Video Sensing Journal of Information Hiding and Multimedia Signal Processing 2014 ISSN 2073-4212 Ubiquitous International Volume 5, Number 1, January 2014 Adaptive Distributed Compressed Video Sensing Xue Zhang 1,3,

More information

IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 58, NO. 5, MAY Note that the term distributed coding in this paper is always employed

IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 58, NO. 5, MAY Note that the term distributed coding in this paper is always employed IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 58, NO. 5, MAY 2010 2875 On Scalable Distributed Coding of Correlated Sources Ankur Saxena, Member, IEEE, and Kenneth Rose, Fellow, IEEE Abstract This paper

More information

Energy Efficient Video Compression for Wireless Sensor Networks *

Energy Efficient Video Compression for Wireless Sensor Networks * 1 Energy Efficient Video Compression for Wireless Sensor Networks * Junaid Jameel Ahmad 1,2, Hassan Aqeel Khan 2, and Syed Ali Khayam 2 1 College of Signals, 2 School of Electrical Engineering & Computer

More information

Constant Bit Rate for Video Streaming Over Packet Switching Networks

Constant Bit Rate for Video Streaming Over Packet Switching Networks International OPEN ACCESS Journal Of Modern Engineering Research (IJMER) Constant Bit Rate for Video Streaming Over Packet Switching Networks Mr. S. P.V Subba rao 1, Y. Renuka Devi 2 Associate professor

More information

Multiple Description H.264 Video Coding with Redundant Pictures

Multiple Description H.264 Video Coding with Redundant Pictures Multiple Description H.4 Video Coding with Redundant Pictures Ivana Radulovic Ecole Polytechnique Fédérale de Lausanne (EPFL) CH-1015 Lausanne, Switzerland ivana.radulovic@epfl.ch Ye-Kui Wang, Stephan

More information

Error Resilient Video Coding Using Unequally Protected Key Pictures

Error Resilient Video Coding Using Unequally Protected Key Pictures Error Resilient Video Coding Using Unequally Protected Key Pictures Ye-Kui Wang 1, Miska M. Hannuksela 2, and Moncef Gabbouj 3 1 Nokia Mobile Software, Tampere, Finland 2 Nokia Research Center, Tampere,

More information

Advanced Video Processing for Future Multimedia Communication Systems

Advanced Video Processing for Future Multimedia Communication Systems Advanced Video Processing for Future Multimedia Communication Systems André Kaup Friedrich-Alexander University Erlangen-Nürnberg Future Multimedia Communication Systems Trend in video to make communication

More information

SYSTEMATIC LOSSY ERROR PROTECTION OF VIDEO SIGNALS

SYSTEMATIC LOSSY ERROR PROTECTION OF VIDEO SIGNALS SYSTEMATIC LOSSY ERROR PROTECTION OF VIDEO SIGNALS A DISSERTATION SUBMITTED TO THE DEPARTMENT OF ELECTRICAL ENGINEERING AND THE COMMITTEE ON GRADUATE STUDIES OF STANFORD UNIVERSITY IN PARTIAL FULFILLMENT

More information

Joint source-channel video coding for H.264 using FEC

Joint source-channel video coding for H.264 using FEC Department of Information Engineering (DEI) University of Padova Italy Joint source-channel video coding for H.264 using FEC Simone Milani simone.milani@dei.unipd.it DEI-University of Padova Gian Antonio

More information

Dual frame motion compensation for a rate switching network

Dual frame motion compensation for a rate switching network Dual frame motion compensation for a rate switching network Vijay Chellappa, Pamela C. Cosman and Geoffrey M. Voelker Dept. of Electrical and Computer Engineering, Dept. of Computer Science and Engineering

More information

UC San Diego UC San Diego Previously Published Works

UC San Diego UC San Diego Previously Published Works UC San Diego UC San Diego Previously Published Works Title Wyner-Ziv Video Coding With Classified Correlation Noise Estimation and Key Frame Coding Mode Selection Permalink https://escholarship.org/uc/item/26n2f9r4

More information

Robust 3-D Video System Based on Modified Prediction Coding and Adaptive Selection Mode Error Concealment Algorithm

Robust 3-D Video System Based on Modified Prediction Coding and Adaptive Selection Mode Error Concealment Algorithm International Journal of Signal Processing Systems Vol. 2, No. 2, December 2014 Robust 3-D Video System Based on Modified Prediction Coding and Adaptive Selection Mode Error Concealment Algorithm Walid

More information

Interleaved Source Coding (ISC) for Predictive Video over ERASURE-Channels

Interleaved Source Coding (ISC) for Predictive Video over ERASURE-Channels Interleaved Source Coding (ISC) for Predictive Video over ERASURE-Channels Jin Young Lee, Member, IEEE and Hayder Radha, Senior Member, IEEE Abstract Packet losses over unreliable networks have a severe

More information

UNBALANCED QUANTIZED MULTI-STATE VIDEO CODING

UNBALANCED QUANTIZED MULTI-STATE VIDEO CODING UNBALANCED QUANTIZED MULTI-STATE VIDEO CODING Sila Ekmekci Flierl, Thomas Sikora +, Pascal Frossard Ecole Polytechnique Fédérale de Lausanne (EPFL) Technical University Berlin + Signal Processing Institute

More information

Skip Length and Inter-Starvation Distance as a Combined Metric to Assess the Quality of Transmitted Video

Skip Length and Inter-Starvation Distance as a Combined Metric to Assess the Quality of Transmitted Video Skip Length and Inter-Starvation Distance as a Combined Metric to Assess the Quality of Transmitted Video Mohamed Hassan, Taha Landolsi, Husameldin Mukhtar, and Tamer Shanableh College of Engineering American

More information

Marie Ramon, François-XavierCoudoux, andmarcgazalet. 1. Introduction

Marie Ramon, François-XavierCoudoux, andmarcgazalet. 1. Introduction Digital Multimedia Broadcasting Volume 2009, Article ID 709813, 7 pages doi:10.1155/2009/709813 Research Article An Adaptive Systematic Lossy Error Protection Scheme for Broadcast Applications Based on

More information

Reduced Decoder Complexity and Latency in Pixel-Domain Wyner-Ziv Video Coders

Reduced Decoder Complexity and Latency in Pixel-Domain Wyner-Ziv Video Coders Reduced Decoder Complexity and Latency in Pixel-Domain Wyner-Ziv Video Coders Marleen Morbee Antoni Roca Josep Prades-Nebot Aleksandra Pižurica Wilfried Philips Abstract In some video coding applications,

More information

ROBUST REGION-OF-INTEREST SCALABLE CODING WITH LEAKY PREDICTION IN H.264/AVC. Qian Chen, Li Song, Xiaokang Yang, Wenjun Zhang

ROBUST REGION-OF-INTEREST SCALABLE CODING WITH LEAKY PREDICTION IN H.264/AVC. Qian Chen, Li Song, Xiaokang Yang, Wenjun Zhang ROBUST REGION-OF-INTEREST SCALABLE CODING WITH LEAKY PREDICTION IN H.264/AVC Qian Chen, Li Song, Xiaokang Yang, Wenjun Zhang Institute of Image Communication & Information Processing Shanghai Jiao Tong

More information

PACKET-SWITCHED networks have become ubiquitous

PACKET-SWITCHED networks have become ubiquitous IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 13, NO. 7, JULY 2004 885 Video Compression for Lossy Packet Networks With Mode Switching and a Dual-Frame Buffer Athanasios Leontaris, Student Member, IEEE,

More information

Error-Resilience Video Transcoding for Wireless Communications

Error-Resilience Video Transcoding for Wireless Communications MITSUBISHI ELECTRIC RESEARCH LABORATORIES http://www.merl.com Error-Resilience Video Transcoding for Wireless Communications Anthony Vetro, Jun Xin, Huifang Sun TR2005-102 August 2005 Abstract Video communication

More information

The H.26L Video Coding Project

The H.26L Video Coding Project The H.26L Video Coding Project New ITU-T Q.6/SG16 (VCEG - Video Coding Experts Group) standardization activity for video compression August 1999: 1 st test model (TML-1) December 2001: 10 th test model

More information

Scalable Foveated Visual Information Coding and Communications

Scalable Foveated Visual Information Coding and Communications Scalable Foveated Visual Information Coding and Communications Ligang Lu,1 Zhou Wang 2 and Alan C. Bovik 2 1 Multimedia Technologies, IBM T. J. Watson Research Center, Yorktown Heights, NY 10598, USA 2

More information

Decoder-driven mode decision in a block-based distributed video codec

Decoder-driven mode decision in a block-based distributed video codec DOI 10.1007/s11042-010-0718-5 Decoder-driven mode decision in a block-based distributed video codec Stefaan Mys Jürgen Slowack Jozef Škorupa Nikos Deligiannis Peter Lambert Adrian Munteanu Rik Van de Walle

More information

HEVC: Future Video Encoding Landscape

HEVC: Future Video Encoding Landscape HEVC: Future Video Encoding Landscape By Dr. Paul Haskell, Vice President R&D at Harmonic nc. 1 ABSTRACT This paper looks at the HEVC video coding standard: possible applications, video compression performance

More information

Popularity-Aware Rate Allocation in Multi-View Video

Popularity-Aware Rate Allocation in Multi-View Video Popularity-Aware Rate Allocation in Multi-View Video Attilio Fiandrotti a, Jacob Chakareski b, Pascal Frossard b a Computer and Control Engineering Department, Politecnico di Torino, Turin, Italy b Signal

More information

Chapter 10 Basic Video Compression Techniques

Chapter 10 Basic Video Compression Techniques Chapter 10 Basic Video Compression Techniques 10.1 Introduction to Video compression 10.2 Video Compression with Motion Compensation 10.3 Video compression standard H.261 10.4 Video compression standard

More information

Wyner-Ziv video coding for wireless lightweight multimedia applications

Wyner-Ziv video coding for wireless lightweight multimedia applications RESEARCH Open Access Wyner-Ziv video coding for wireless lightweight multimedia applications Nikos Deligiannis,2*, Frederik Verbist,2, Athanassios C Iossifides 3, Jürgen Slowack 2,4, Rik Van de Walle 2,4,

More information

The H.263+ Video Coding Standard: Complexity and Performance

The H.263+ Video Coding Standard: Complexity and Performance The H.263+ Video Coding Standard: Complexity and Performance Berna Erol (bernae@ee.ubc.ca), Michael Gallant (mikeg@ee.ubc.ca), Guy C t (guyc@ee.ubc.ca), and Faouzi Kossentini (faouzi@ee.ubc.ca) Department

More information

1. INTRODUCTION. Index Terms Video Transcoding, Video Streaming, Frame skipping, Interpolation frame, Decoder, Encoder.

1. INTRODUCTION. Index Terms Video Transcoding, Video Streaming, Frame skipping, Interpolation frame, Decoder, Encoder. Video Streaming Based on Frame Skipping and Interpolation Techniques Fadlallah Ali Fadlallah Department of Computer Science Sudan University of Science and Technology Khartoum-SUDAN fadali@sustech.edu

More information

Bit Rate Control for Video Transmission Over Wireless Networks

Bit Rate Control for Video Transmission Over Wireless Networks Indian Journal of Science and Technology, Vol 9(S), DOI: 0.75/ijst/06/v9iS/05, December 06 ISSN (Print) : 097-686 ISSN (Online) : 097-5 Bit Rate Control for Video Transmission Over Wireless Networks K.

More information

Rate-Adaptive Codes for Distributed Source Coding

Rate-Adaptive Codes for Distributed Source Coding Rate-Adaptive Codes for Distributed Source Coding David Varodayan, Anne Aaron and Bernd Girod Information Systems Lab., Dept. of Electrical Engineering Stanford University, Stanford, CA 94305, USA Abstract

More information

Error Concealment for SNR Scalable Video Coding

Error Concealment for SNR Scalable Video Coding Error Concealment for SNR Scalable Video Coding M. M. Ghandi and M. Ghanbari University of Essex, Wivenhoe Park, Colchester, UK, CO4 3SQ. Emails: (mahdi,ghan)@essex.ac.uk Abstract This paper proposes an

More information

ROBUST ADAPTIVE INTRA REFRESH FOR MULTIVIEW VIDEO

ROBUST ADAPTIVE INTRA REFRESH FOR MULTIVIEW VIDEO ROBUST ADAPTIVE INTRA REFRESH FOR MULTIVIEW VIDEO Sagir Lawan1 and Abdul H. Sadka2 1and 2 Department of Electronic and Computer Engineering, Brunel University, London, UK ABSTRACT Transmission error propagation

More information

Analysis of Packet Loss for Compressed Video: Does Burst-Length Matter?

Analysis of Packet Loss for Compressed Video: Does Burst-Length Matter? Analysis of Packet Loss for Compressed Video: Does Burst-Length Matter? Yi J. Liang 1, John G. Apostolopoulos, Bernd Girod 1 Mobile and Media Systems Laboratory HP Laboratories Palo Alto HPL-22-331 November

More information

Introduction to Video Compression Techniques. Slides courtesy of Tay Vaughan Making Multimedia Work

Introduction to Video Compression Techniques. Slides courtesy of Tay Vaughan Making Multimedia Work Introduction to Video Compression Techniques Slides courtesy of Tay Vaughan Making Multimedia Work Agenda Video Compression Overview Motivation for creating standards What do the standards specify Brief

More information

ARTICLE IN PRESS. Signal Processing: Image Communication

ARTICLE IN PRESS. Signal Processing: Image Communication Signal Processing: Image Communication 23 (2008) 677 691 Contents lists available at ScienceDirect Signal Processing: Image Communication journal homepage: www.elsevier.com/locate/image H.264/AVC-based

More information

University of Bristol - Explore Bristol Research. Peer reviewed version. Link to published version (if available): /ISCAS.2005.

University of Bristol - Explore Bristol Research. Peer reviewed version. Link to published version (if available): /ISCAS.2005. Wang, D., Canagarajah, CN., & Bull, DR. (2005). S frame design for multiple description video coding. In IEEE International Symposium on Circuits and Systems (ISCAS) Kobe, Japan (Vol. 3, pp. 19 - ). Institute

More information

ARTICLE IN PRESS. Signal Processing: Image Communication

ARTICLE IN PRESS. Signal Processing: Image Communication Signal Processing: Image Communication 23 (2008) 339 352 Contents lists available at ScienceDirect Signal Processing: Image Communication journal homepage: www.elsevier.com/locate/image Distributed Video

More information

Dual frame motion compensation for a rate switching network

Dual frame motion compensation for a rate switching network Dual frame motion compensation for a rate switching network Vijay Chellappa, Pamela C. Cosman and Geoffrey M. Voelker Dept. of Electrical and Computer Engineering, Dept. of Computer Science and Engineering

More information

Coding. Multiple Description. Packet networks [1][2] a new technology for video streaming over the Internet. Andrea Vitali STMicroelectronics

Coding. Multiple Description. Packet networks [1][2] a new technology for video streaming over the Internet. Andrea Vitali STMicroelectronics Coding Multiple Description a new technology for video streaming over the Internet Andrea Vitali STMicroelectronics The Internet is growing quickly as a network of heterogeneous communication networks.

More information

Multimedia Communications. Image and Video compression

Multimedia Communications. Image and Video compression Multimedia Communications Image and Video compression JPEG2000 JPEG2000: is based on wavelet decomposition two types of wavelet filters one similar to what discussed in Chapter 14 and the other one generates

More information

OPEN STANDARD GIGABIT ETHERNET LOW LATENCY VIDEO DISTRIBUTION ARCHITECTURE

OPEN STANDARD GIGABIT ETHERNET LOW LATENCY VIDEO DISTRIBUTION ARCHITECTURE 2012 NDIA GROUND VEHICLE SYSTEMS ENGINEERING AND TECHNOLOGY SYMPOSIUM VEHICLE ELECTRONICS AND ARCHITECTURE (VEA) MINI-SYMPOSIUM AUGUST 14-16, MICHIGAN OPEN STANDARD GIGABIT ETHERNET LOW LATENCY VIDEO DISTRIBUTION

More information

Compressed-Sensing-Enabled Video Streaming for Wireless Multimedia Sensor Networks Abstract:

Compressed-Sensing-Enabled Video Streaming for Wireless Multimedia Sensor Networks Abstract: Compressed-Sensing-Enabled Video Streaming for Wireless Multimedia Sensor Networks Abstract: This article1 presents the design of a networked system for joint compression, rate control and error correction

More information

Modeling and Evaluating Feedback-Based Error Control for Video Transfer

Modeling and Evaluating Feedback-Based Error Control for Video Transfer Modeling and Evaluating Feedback-Based Error Control for Video Transfer by Yubing Wang A Dissertation Submitted to the Faculty of the WORCESTER POLYTECHNIC INSTITUTE In partial fulfillment of the Requirements

More information

Video coding standards

Video coding standards Video coding standards Video signals represent sequences of images or frames which can be transmitted with a rate from 5 to 60 frames per second (fps), that provides the illusion of motion in the displayed

More information

Distributed Video Coding: Selecting the Most Promising Application Scenarios

Distributed Video Coding: Selecting the Most Promising Application Scenarios Distributed Video Coding: Selecting the Most Promising Application Scenarios Fernando Pereira (Instituto Superior Técnico Instituto de Telecomunicações, Portugal) Luis Torres (Technical University of Catalonia,

More information

MPEG-2. ISO/IEC (or ITU-T H.262)

MPEG-2. ISO/IEC (or ITU-T H.262) 1 ISO/IEC 13818-2 (or ITU-T H.262) High quality encoding of interlaced video at 4-15 Mbps for digital video broadcast TV and digital storage media Applications Broadcast TV, Satellite TV, CATV, HDTV, video

More information

17 October About H.265/HEVC. Things you should know about the new encoding.

17 October About H.265/HEVC. Things you should know about the new encoding. 17 October 2014 About H.265/HEVC. Things you should know about the new encoding Axis view on H.265/HEVC > Axis wants to see appropriate performance improvement in the H.265 technology before start rolling

More information

Contents. xv xxi xxiii xxiv. 1 Introduction 1 References 4

Contents. xv xxi xxiii xxiv. 1 Introduction 1 References 4 Contents List of figures List of tables Preface Acknowledgements xv xxi xxiii xxiv 1 Introduction 1 References 4 2 Digital video 5 2.1 Introduction 5 2.2 Analogue television 5 2.3 Interlace 7 2.4 Picture

More information

Scalable multiple description coding of video sequences

Scalable multiple description coding of video sequences Scalable multiple description coding of video sequences Marco Folli, and Lorenzo Favalli Electronics Department University of Pavia, Via Ferrata 1, 100 Pavia, Italy Email: marco.folli@unipv.it, lorenzo.favalli@unipv.it

More information

Performance Evaluation of Error Resilience Techniques in H.264/AVC Standard

Performance Evaluation of Error Resilience Techniques in H.264/AVC Standard Performance Evaluation of Error Resilience Techniques in H.264/AVC Standard Ram Narayan Dubey Masters in Communication Systems Dept of ECE, IIT-R, India Varun Gunnala Masters in Communication Systems Dept

More information

Multimedia Communications. Video compression

Multimedia Communications. Video compression Multimedia Communications Video compression Video compression Of all the different sources of data, video produces the largest amount of data There are some differences in our perception with regard to

More information

Error concealment techniques in H.264 video transmission over wireless networks

Error concealment techniques in H.264 video transmission over wireless networks Error concealment techniques in H.264 video transmission over wireless networks M U L T I M E D I A P R O C E S S I N G ( E E 5 3 5 9 ) S P R I N G 2 0 1 1 D R. K. R. R A O F I N A L R E P O R T Murtaza

More information

Research Article Spatial Multiple Description Coding for Scalable Video Streams

Research Article Spatial Multiple Description Coding for Scalable Video Streams Digital Multimedia Broadcasting, Article ID 132621, 8 pages http://dx.doi.org/10.1155/2014/132621 Research Article Spatial Multiple Description Coding for Scalable Video Streams Roya Choupani, 1 Stephan

More information

AN UNEQUAL ERROR PROTECTION SCHEME FOR MULTIPLE INPUT MULTIPLE OUTPUT SYSTEMS. M. Farooq Sabir, Robert W. Heath and Alan C. Bovik

AN UNEQUAL ERROR PROTECTION SCHEME FOR MULTIPLE INPUT MULTIPLE OUTPUT SYSTEMS. M. Farooq Sabir, Robert W. Heath and Alan C. Bovik AN UNEQUAL ERROR PROTECTION SCHEME FOR MULTIPLE INPUT MULTIPLE OUTPUT SYSTEMS M. Farooq Sabir, Robert W. Heath and Alan C. Bovik Dept. of Electrical and Comp. Engg., The University of Texas at Austin,

More information

CODING EFFICIENCY IMPROVEMENT FOR SVC BROADCAST IN THE CONTEXT OF THE EMERGING DVB STANDARDIZATION

CODING EFFICIENCY IMPROVEMENT FOR SVC BROADCAST IN THE CONTEXT OF THE EMERGING DVB STANDARDIZATION 17th European Signal Processing Conference (EUSIPCO 2009) Glasgow, Scotland, August 24-28, 2009 CODING EFFICIENCY IMPROVEMENT FOR SVC BROADCAST IN THE CONTEXT OF THE EMERGING DVB STANDARDIZATION Heiko

More information

Video (Fundamentals, Compression Techniques & Standards) Hamid R. Rabiee Mostafa Salehi, Fatemeh Dabiran, Hoda Ayatollahi Spring 2011

Video (Fundamentals, Compression Techniques & Standards) Hamid R. Rabiee Mostafa Salehi, Fatemeh Dabiran, Hoda Ayatollahi Spring 2011 Video (Fundamentals, Compression Techniques & Standards) Hamid R. Rabiee Mostafa Salehi, Fatemeh Dabiran, Hoda Ayatollahi Spring 2011 Outlines Frame Types Color Video Compression Techniques Video Coding

More information

An Overview of Video Coding Algorithms

An Overview of Video Coding Algorithms An Overview of Video Coding Algorithms Prof. Ja-Ling Wu Department of Computer Science and Information Engineering National Taiwan University Video coding can be viewed as image compression with a temporal

More information

Adaptive Key Frame Selection for Efficient Video Coding

Adaptive Key Frame Selection for Efficient Video Coding Adaptive Key Frame Selection for Efficient Video Coding Jaebum Jun, Sunyoung Lee, Zanming He, Myungjung Lee, and Euee S. Jang Digital Media Lab., Hanyang University 17 Haengdang-dong, Seongdong-gu, Seoul,

More information

ROBUST IMAGE AND VIDEO CODING WITH ADAPTIVE RATE CONTROL

ROBUST IMAGE AND VIDEO CODING WITH ADAPTIVE RATE CONTROL University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Theses, Dissertations, & Student Research in Computer Electronics & Engineering Electrical & Computer Engineering, Department

More information

CONTEMPORARY hybrid video codecs use motion-compensated

CONTEMPORARY hybrid video codecs use motion-compensated IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, VOL. 18, NO. 2, FEBRUARY 2008 249 Transactions Letters Dual Frame Motion Compensation With Uneven Quality Assignment Vijay Chellappa, Pamela

More information

Understanding Compression Technologies for HD and Megapixel Surveillance

Understanding Compression Technologies for HD and Megapixel Surveillance When the security industry began the transition from using VHS tapes to hard disks for video surveillance storage, the question of how to compress and store video became a top consideration for video surveillance

More information

Fast MBAFF/PAFF Motion Estimation and Mode Decision Scheme for H.264

Fast MBAFF/PAFF Motion Estimation and Mode Decision Scheme for H.264 Fast MBAFF/PAFF Motion Estimation and Mode Decision Scheme for H.264 Ju-Heon Seo, Sang-Mi Kim, Jong-Ki Han, Nonmember Abstract-- In the H.264, MBAFF (Macroblock adaptive frame/field) and PAFF (Picture

More information

P1: OTA/XYZ P2: ABC c01 JWBK457-Richardson March 22, :45 Printer Name: Yet to Come

P1: OTA/XYZ P2: ABC c01 JWBK457-Richardson March 22, :45 Printer Name: Yet to Come 1 Introduction 1.1 A change of scene 2000: Most viewers receive analogue television via terrestrial, cable or satellite transmission. VHS video tapes are the principal medium for recording and playing

More information

Overview: Video Coding Standards

Overview: Video Coding Standards Overview: Video Coding Standards Video coding standards: applications and common structure ITU-T Rec. H.261 ISO/IEC MPEG-1 ISO/IEC MPEG-2 State-of-the-art: H.264/AVC Video Coding Standards no. 1 Applications

More information

Motion Re-estimation for MPEG-2 to MPEG-4 Simple Profile Transcoding. Abstract. I. Introduction

Motion Re-estimation for MPEG-2 to MPEG-4 Simple Profile Transcoding. Abstract. I. Introduction Motion Re-estimation for MPEG-2 to MPEG-4 Simple Profile Transcoding Jun Xin, Ming-Ting Sun*, and Kangwook Chun** *Department of Electrical Engineering, University of Washington **Samsung Electronics Co.

More information

GLOBAL DISPARITY COMPENSATION FOR MULTI-VIEW VIDEO CODING. Kwan-Jung Oh and Yo-Sung Ho

GLOBAL DISPARITY COMPENSATION FOR MULTI-VIEW VIDEO CODING. Kwan-Jung Oh and Yo-Sung Ho GLOBAL DISPARITY COMPENSATION FOR MULTI-VIEW VIDEO CODING Kwan-Jung Oh and Yo-Sung Ho Department of Information and Communications Gwangju Institute of Science and Technolog (GIST) 1 Orong-dong Buk-gu,

More information

Integrated end-end buffer management and congestion control for scalable video communications

Integrated end-end buffer management and congestion control for scalable video communications 1 Integrated end-end buffer management and congestion control for scalable video communications Ivan V. Bajić, Omesh Tickoo, Anand Balan, Shivkumar Kalyanaraman, and John W. Woods Authors are with the

More information

Introduction. Packet Loss Recovery for Streaming Video. Introduction (2) Outline. Problem Description. Model (Outline)

Introduction. Packet Loss Recovery for Streaming Video. Introduction (2) Outline. Problem Description. Model (Outline) Packet Loss Recovery for Streaming Video N. Feamster and H. Balakrishnan MIT In Workshop on Packet Video (PV) Pittsburg, April 2002 Introduction (1) Streaming is growing Commercial streaming successful

More information