1 / 9

Changing Landscape of Multimedia Applications

Changing Landscape of Multimedia Applications. Today: Downlink Video Broadcast. Tomorrow: Uplink Video Transmission. DFD (Displaced Frame Difference). Motion search range. +. Motion Vector. Previous frame. Current frame. Contemporary Video Coding Standards.

nakeisha
Download Presentation

Changing Landscape of Multimedia Applications

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Changing Landscape of Multimedia Applications Today: Downlink Video Broadcast Tomorrow: Uplink Video Transmission

  2. DFD (Displaced Frame Difference) Motion search range + Motion Vector Previous frame Current frame Contemporary Video Coding Standards • Motion-Compensated Predictive Coding (MPEG/H.26) • High compression efficiency • Rigid complexity partition between encoder (heavy) & decoder (light) • High fragility to transmission losses • Image Coding (Motion JPEG) • Low complexity • High robustness to transmission losses • Low compression efficiency

  3. Heavy PRISM Uplink Decoder Heavy PRISM Downlink Encoder Trans-coding Proxy Light PRISM Uplink Encoder Light PRISM Downlink Decoder Rethinking Video Over Wireless Challenges: • Low bandwidths  high compression efficiency • Limited handheld battery power low end-device complexity • Lossy wireless medium robustness to transmission losses New Architecture: PRISM (Power-efficient, Robust, hIgh-compression Syndrome-based Multimedia coding) High compression efficiency Flexible partition of complexity between encoder & decoder Inbuilt robustness to channel loss Backward compatibility with existing video standards Puri & Ramchandran, Allerton ’02

  4. Background: Distributed Source Coding Source Coding with side-information (Slepian–Wolf, Wyner-Ziv) ^ • X and Y are correlated sources • Y is available only at decoder X X Encoder Decoder Y Exploit side-information Y at the decoder while encoding X No MSE performance loss over case when Y is available at both encoder and decoder when innovations is Gaussian For the video coding case, X is the block to be coded and the side-information Y consists of the previously decoded blocks in the frame memory

  5. Y1’ YM’ . . . … Motion Vector … X X … Quantized … DFD Y1 Y1 YM YM . . . . . . Y1’ YM’ . . . Predictive Decoder PRISM Decoder Predictive Encoder PRISM Encoder ? X X Motion-Free Encoding? • The encoder does not have access to Y1’, Y2’, etc • Neither the encoder nor the decoder knows the correct side-information • Can decoding work? • Yes! • A “modified” Wyner-Ziv paradigm is needed (Ishwar, Prabhakaran, & Ramchandran ICIP ’03.)

  6. Y1’ Decoding failure Wyner-Ziv Decoder . . . YT’ X Wyner-Ziv Decoder bin index YM’ . . . Decoding failure Wyner-Ziv Encoder Wyner-Ziv Decoder X PRISM Need concept of “motion compensation at decoder”! Need mechanism to detect decoding failure In theory: joint typicality (statistical consistency) In practice: use CRC Robustness Comparisons: • Predictive Coding: channel errors lead to prediction mismatch and drift • PRISM: drift stopped if syndrome code is “strong enough”:Targeted noise ≥ Correlation Noise + Induced Channel Noise + Quant. Noise

  7. Auxiliary-Channel Coset Index Auxiliary-Channel Encoder Auxiliary-Channel Decoder Final reconstruction Wireless Channel X MPEG/H.26X Decoder MPEG/H.26x Encoder Xmain Wireless Channel MPEG/H.26x bit-stream ^ X Standards-Compliant Auxiliary-Channel • Secondary description of video sent over auxiliary-channel. • Need to find statistics of correlation noiseZ = X – Xmain. • Can leverage algorithm of Zhang, Regunathan and Rose (Asilomar ’99) to develop recursive correlation estimation algorithm. (Wang, Majumdar, Ramchandran, and Garudadri: PCS ’04.) • Auxiliary channel allows drift correction without intra-refresh.

  8. Results • Channel simulator provided by Qualcomm Inc. conforming to a CDMA 2000 1x standard. • Performance comparison among 3 systems: • H.263+ bitstream with 20% extra rate for FEC (RS codes) • H.263+ bitstream with 20% extra rate for standard-compliant auxiliary channel • PRISM • Standard-compliant auxiliary channel version outperforms H.263+FEC by 2.5-4 dB between error rates of 2-10%. • PRISM outperforms H.263+FEC by 6-8 dB between error rates of 2-10%. H.263+ with FEC H.263+ with Auxiliary Channel PRISM Stefan, 352x240, 15fps, 2200 kbps, 8% error rate

  9. PRISM for Wireless Video Broadcast Yb (“bad” side-information) Decoder Bad Xb Rate = R Encoder X • Broadcast source coding studied in information theory literature. (Heegard & Berger, IT’85, Steinberg & Merhav IT’04) • Lossy channel: need broadcast source-channel coding view. • Can use PRISM constructions. (Majumdar & Ramchandran, ICIP ’04) • No need to deterministically track Yb and Yg at encoder. • No need for multiple prediction loops  complexity savings. • Multiple side-informations at each decoder  motion search at each decoder. • Standards-compliant implementations possibly using the auxiliary channel setup. (Wang, Majumdar, & Ramchandran, ICASSP ’05) Decoder Good Xg Rate = ∆R Yg (“good” side-information)

More Related