PhD Project Kristof Denolf

Coding and Complexity Efficiency Relationship of Hybrid MC/DCT Video Codecs



During the complete history of video coding, removing the redundant information in video data while still preserving the best possible quality has always been the primary goal: the search for the highest coding efficiency. The work of the Joint Video Team (a collaboration of ISO/MPEG and ITU/VCEG) to standardize a new generation video coding proves this search continues today. During the last years, the implementation cost of these compression systems became more and more important to avoid falling into the trap of developing an extremely efficient coding algorithm never able to fit into a realistic design. Moreover, the large complexity variation between average usage cases and the most demanding scenario excludes worst-case implementations and hence requires compromises.

Prior art in Network Quality of Service (QoS) typically deals with the bandwidth versus quality trade-off. This PhD project adds an additional dimension: the impact of limited processing resources on the quality (Terminal QoS). Hence, the processing load will be combined with the coding efficiency to analyse the relation of the bitrate, the quality and the complexity of a hybrid Motion Compensated/Discrete Cosine Transform (MC/DCT) video codec. The goal is not to improve the compression efficiency, but rather interpret the efficiency of existing codecs in a broader and more complete way by including complexity issues. More specifically, the focus will be on MPEG-4 video, including the new part 10: the Avanced Video Codec (AVC).


A solid study of the bitrate/quality/complexity cost relations requires first their proper definition. For none of them this definition is trivial. Quality, complexity and even bitrate can each individually, only be faithfully characterised in a multi-dimensional space to allow for generality and completeness. Weighting and combining multiple dimensions of one component for simplified analysis, reduces the level of detail, but at the same time requires a thorough understanding of the goals to achieve, i.e. a meaningful compromise between the cost axes. Eventually, a three dimensional quality\complexity\bitrate plot is instantiated for a particular implementation platform and known network parameters.


The proliferation of video coding applications and the diversity in bandwidth and processing resources of content consumers steer the analysis of the quality, bitrate and complexity when scaling a video codec by varying the quantization degree, the temporal and spatial resolution. From the cloud of operation points, a pareto surface with optimal codec settings can be extracted. The specific issues related to different usage scenarios require two distinct approaches in this study: first a point-to-point connection, then extend to a multi-user environment.