Distributed Coding for Video Services

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Over the past decade several video coding technologies have emerged to achieve great commercial success and it is widely expected that digital video systems will completely replace all existing traditional analogue based video systems during the next decade. DISCOVER will address the development of several advanced digital video coding technologies which are very likely to represent a breakthrough in new video coding application scenarios.

Until now video coding research and standardization have been adopting a video coding paradigm where it is the task of the encoder to explore the source statistics, leading to a complexity balance where complex encoders interact with simpler decoders. This paradigm is strongly dominated and determined by applications such as broadcasting, video on demand, and video streaming. Distributed Video Coding (DVC) adopts a completely different coding paradigm by giving the decoder the task to exploit - partly or wholly - the source statistics to achieve efficient compression. This change of paradigm also moves the encoder-decoder complexity balance, allowing the provision of efficient compression solutions with simple encoders and complex decoders.

This new coding paradigm, never considered by any video coding standard, is particularly adequate to emerging applications such as wireless video cameras and wireless low-power surveillance networks, disposable video cameras, certain medical applications, sensor networks, multi-view image acquisition, networked camcorders, etc., where low complexity encoders are a must because memory, computational power, and energy are scarce.

The objective of DISCOVER is to explore and propose new video coding schemes and tools in the area of Distributed Video Coding with a strong potential for new applications, targeting new advances in coding efficiency, error resiliency, scalability, and model based-video coding thus paving the way for a breakthrough regarding the next video coding generation.

DVC is based on the Slepian-Wolf and Wyner-Ziv theorems. These theorems state that it is possible to compress two statistically dependent signals in a distributed way (separate encoding, jointly decoding) using a rate equal to that used in a system where the signals are encoded and decoded together.
Current approaches mostly implement the unsymmetrical case, where the two signals are coded with different bitrates. The block diagram of the architecture used in DISCOVER is shown in Figure 1.

DVC Architecture
Figure 1: DVC Architecture

At the encoder, the sequence is divided into key frames and Wyner-Ziv (WZ) frames controlled by the group-of-picture (GOP) size (e.g. at GOP size 4 every fourth frame is coded as key frame). The key frames are coded with a conventional intra frame coder (e.g. H.264) and are used to estimate the WZ frame at the decoder (so called side information).
Each WZ frame is encoded independently of the key frames and of the other WZ frames. First, the pixels of the WZ frame are quantised. The stream of quantised symbols is fed into the Turbo Coder, which represents the Slepian-Wolf part of the architecture. The systematic bits are discarded and only the parity bits of the two convolutional encoders inside the Turbo Encoder are stored in the buffer. To be rate compatible, the encoder sends only a subset of the parity bits (rate compatible punctured turbo code). The decoder uses the parity bits to reconstruct the frame from the side information. If the decoder cannot properly decode the current frame, more bits are requested via the back channel. Therefore, changing statistics between the side information and the original frame can be handled. After Turbo Decoding, the transform coefficients are reconstructed and transformed to the pixel domain.

Show all publications
  • Fernando Pereira, Luis Torres, Christine Guillemot, Touradj Ebrahimi, Riccardo Leonardi, Sven Klomp
    Distributed Video Coding: Selecting the most promising application scenarios
    Signal Processing: Image Communication, Elsevier B.V., Vol. 23, No. 5, pp. 339-352, June 2008
  • Xavi Artigas, Joao Ascenso, Marco Dalai, Sven Klomp, Denis Kubasov, Mourad Ouaret
    The Discover Codec: Architecture, Techniques And Evaluation
    Picture Coding Symposium, Lisboa, Portugal, November 2007
  • Yuri Vatis, Sven Klomp, Jörn Ostermann
    Inverse Bit Plane Decoding Order for Turbo Code based Distributed Video Coding
    Proc. ICIP 2007, IEEE International Conference on Image Processing, pp. II - 1 - II - 4, San Antonio, USA, September 2007