Trends and challenges in video coding

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Trends and challenges
in video coding
Prof. Dr. Touradj Ebrahimi
VISNET-II Summer School
KOC University, Istanbul, June 15-19 2009

Multimedia Signal Processing Group
Swiss Federal Institute of Technology, Lausanne

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Outline

•  First things first…
•  Trends in video coding
•  Challenges in video coding
•  Some last words…


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Outline



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First things first…

•  Often the future is not the result of one,
but many trends occurring in parallel,
which at times, when interacting, can lead
to results not easily predictable when
considering only one or a subset of such
trends


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•  Is there a Moore’s law of compression?


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•  Not only between different technologies…


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•  … but also for a same technology
MPEG-2 video


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Outline

•  Trends in video coding…


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Trends in video coding

•  Trends in video coding are influenced by:
–  Trends in the type/nature of content
–  Trends in technologies/products
–  Trends in applications/services


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Trends in type/nature of content

•  Explosion in all dimensions:
–  Spatial resolution (QCIF to HD to UHD)
–  Temporal resolution (25 to 60 to 200 Hz)
–  Spatial dimensions (2D to 3D to Holography)
–  Number of components (Y to RGB to RG1G2B)
–  Dynamic range of each component (8 to 16 bpp
to floating point)
•  Increasing number of movies use computer
graphics generated content


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Trends in technologies/products

•  Capture
•  CPU/DSP
•  Communication channels
•  Storage
•  Display/Printing


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Trends in applications/services

•  Prosumer (producer/consumer) models
→  Social networks: Youtube/Facebook/Twitter
→  …
•  New types of access to content
→  Podcasting
→  P2P
→  IPTV
→  …


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Trends in video coding

•  Evolutions of existing architectures/tools
•  New tools in existing/extended architectures
•  Disruptive architectures/tools


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Evolutions of existing architectures/tools

•  An example… H.265/KTA in ITU-T


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•  H.265 is a long-term video coding standard, ‘launched’ by ITU-T VCEG.
•  Not yet formalized but VCEG keeps seeking proposals and information regarding the
possibility of a major performance gain to justify the step from H.264 to H.265.
•  Though the necessary scope of H.265 is yet largely to be determined, it is agreed that
among the goals will be:
–  High coding efficiency, e.g., two times compared with H.264/AVC
–  Computational efficiency, considering both encoder and decoder
–  Loss/error robustness
–  Network friendliness
•  So far, contributions to VCEG have mainly focused on improving coding
efficiency.
•  To better evaluate these contributions and retain progress, the KTA (Key
Technical Area) has been developed as the software platform, using JM11 as
the baseline and continuously integrating promising tools.


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•  Inter prediction
–  Adaptive interpolation filter (AIF)
  2-D non-separable AIF (AD08, AE16)
  Separable AIF (COM16-C219, AG10)
  Directional AIF (DAIF) (AG21, AG22, AH17, AH18)
  Enhanced DAIF (E-DAIF) (AI12, COM16-C125, COM16-C126)
  Enhanced AIF (EAIF) (C464, AI38, AJ30)
  Switch interpolation filters with offsets (SIFO) (C463, AI35, AJ29, COM16-C126)
  High precision filter (HPF) (AI33)
  Single-pass encoding (AJ29, AK26)

–  1/8-pel motion compensated prediction (MCP) (AD09)
–  Extended MCP block size (COM16-C123)
–  Competition-based MV prediction (AC06)


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•  Transform and Quantization
–  Mode-dependent directional transform (MDDT) (AF15,
AG11, AH20, AJ24, AI36)
–  Very large block transform (COM16-C123)
–  Adaptive prediction error coding (APEC) (AB06, AD07,
AE15)
–  Adaptive quantization matrix selection (AQMS) (AC07,
AD06, AF08, AI19)
–  Rate-distortion optimized quantization (RDO-Q) (AH21)


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•  Entropy coding
–  Parallel CABAC (COM16-C405, AI32)
•  In-loop filter
–  Block-based adaptive loop filter (BALF) (AI18, AJ13)
–  Quadtree-based adaptive loop filter (QALF) (COM16-
C181, AK22)
•  Post filter (AI34, COM16–C128)
•  Internal bit depth increasing (IBDI) (AE13, AF07)


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New tools in existing/extended architectures…

•  An example… FTV in MPEG


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•  Synthesize a continuum of views based on a limited set of views
•  Specify a format that fixes the rate, but allows arbitrarily large
number of views to be rendered


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•  Extend MVC framework to include multi-view video plus depth


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Disruptive architectures/tools…

•  An example… Compressive Sensing


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The signal x is compressible if
the α representation has just a
few large coefficients and
many small coefficients.
from Baraniuk, dsp.rice.edu/cs


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y=Φx=ΦΨs=Θs

•  Compressive sensing addresses the traditional inefficiencies by
directly acquiring a compressed signal representation without going
through the intermediate stage of acquiring N samples. The
measurement process is not adaptive, meaning that Φ is fixed and
does not depend on the signal x.


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Other trends in video coding


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X-lets

•  Better exploit 2D (nD) singularities


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‘rugby’ 4.7 Mbit/s AVC/H.264


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‘rugby’ 4.7 Mbit/s AVC/H.264 + texture synthesis


Efforts in next generation image/video coding 33
standardization
•  JPEG: Advanced Image Coding – AIC
•  MPEG: High performance Video Coding – HVC
•  VCEG: Next Generation Video Coding – NGVC

Potential mergers/synergies in some of the above
efforts are under discussion …


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Outline



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Content representation challenge

•  Which representation can potentially result in huge
coding gains
–  Xlets
–  Compressive sensing
–  Texture analysis/synthesis
–  …
•  What video coding schemes perform best to compress
new content type
–  Ultra High Definition
–  3D
–  HDR
–  Holography
–  …


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Visual perception challenge

•  How to measure quality in 2D/3D video?
–  Subjective quality assessment methodologies
–  Objective quality metrics
–  Quality of Experience
•  How to inject some more efficient perceptual
coding tools in video coding?
–  Perceptual focus of attention
–  Perceptual masking
–  Perceptual pre-/post- processing
–  …


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Applications challenge

•  What are the killer applications that
require alternative video compression
methods with significant added value?
–  P2P
–  Low cost/power encoders
–  Coding schemes reducing stream switching
delay
–  Coding schemes taking into account potential
post-processing/interaction by users
–  …

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Other challenges

•  Video often has an audio that goes with it:
–  How to take advantage of AV correlation
•  How to take better advantage of source/channel/
network synergies and interactions
•  How to take advantage of context in video
coding
•  How to take better advantage of computer
vision, content annotation, search and retrieval
in video compression
•  …


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Outline



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Some last words

•  Prediction is very difficult, especially about the future
–  Niels Bohr (1885-1962): Physics Nobel Prize Winner 1922
•  Scientific and technological considerations are not the
only factors which will decide the future of video coding
–  Intellectual property complexities
–  Policies
–  Industrial/Economic interests
–  …
•  Content is still The King!


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Thanks for your attention !
Questions, discussions, …

Acknowledgement goes to many identified and unidentified individuals from whom some of the
materials presented here come from …


Trends and challenges in video coding

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