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“Dependent R-D Modeling for H.264/SVC Bit Allocation”
by Yongjin Cho
May 2010
In this research, we investigate model-based bit allocation algorithms for H.264/SVC, which is newly standardized as a scalable extension of H.264/AVC. Despite its importance in video coding, inter-dependency between coding units is often indirectly addressed in conventional single layer bit allocation algorithms. This simplified treatment is adopted due to the complexity involved in its explicit consideration. In H.264/SVC, inter-dependency between coding units becomes even more involved and the development of an optimal bit allocation algorithm imposes an even higher challenge.
To address the bit allocation problem for H.264/SVC, we study dependent rate and distortion (R-D) models for temporal and quality scalabilities of H.264/SVC. Traditional R-D models represent rate and distortion characteristics as functions of quantizationparameter (QP), known as the Q-domain analysis, or the percentage of zero transform coefficients, known as the rho-domain analysis. Unlike previous models, we examine dependent R-D characteristics based on the self-domain (S-domain) analysis (namely, R- and D-domain analysis for the rate and the distortion characteristics, respectively), where the R-D characteristics of a dependent coding unit are expressed as the R-D characteristics of its reference and/or base layers. With the proposed R-D models, the complex dependent R-D characteristics can be simplified to be a linear sum of functions of a single parameter. As a result, the bit allocation problem can be solved elegantly.
The temporal dependency of the video signal is first studied. According to the self D-domain study, the distortion of a coding unit is subject to temporal dependency. In contrast, its rate is relatively independent of its references. This leads to a linear dependent distortion model for the temporal scalability. Then, the research is extended to the quality scalability. Contrary to the temporal-layer case, the self R-domain analysis reveals inter-dependency of the rate characteristics. On the other hand, its distortion is independent of those in the preceding layers. For this reason, the quality-layer dependent rate is modeled as the linear sum of base layer rate functions. The performance of the proposed dependent R-D models is verified by comparing their R-D estimation results with actual R-D data. After the initial study on the dependent R-D models, we analyzed the proposed R-D models to understand the physical meaning of the model parameters. We could learn from the analysis that the model parameters convey important information about the inter-layer dependence in the T-Q scalability.
We conduct studies on two bit allocation algorithms, which are formulated as the Lagrangian optimization problem. First, we investigate a temporal layer bit allocation problem based on its dependent distortion model. Then, we examine the joint quality-temporal layer bit allocation problem by combining temporal and quality layer R-D models. One important advantage of the proposed R-D models is that they allow an analytical solution to the Lagrange equation. With the proposed algorithms, both bit allocation problems are numerically solved at significantly reduced complexity. It is shown by experimental results that the proposed algorithms could produce more efficient scalable bit streams than those by the H.264/SVC reference software codec (JSVM) at various bit rates with different types of test sequences. Moreover, the coding gain of each scalable layer, i.e., T or Q layer, exceeds that obtained by the JSVM benchmark.
The purpose of the R-D characteristics modeling is to develop an efficient and effective rate control algorithm for a video coder. Even though the bit allocation algorithms introduced in the first part of the thesis achieve better performance than the JSVM benchmark, their usage is limited to off-line encoding scenarios. To address the issue, we also conduct study the simplification of the bit allocation algorithms considering real-time encoding scenarios. The performance of the proposed is verified by experimental results in comparison with the JSVM benchmark.
Finally, we also examine the rate control of compressed scalable video under network based video application scenarios. We employ cross-layer approach to the design of a wireless video streaming algorithm. Beginning with a through review on the cross-layer design principles, we identified major challenges and issues with the cross-layer design approach in the realistic application scenarios and they could be well addressed by the proposed algorithm. The computer simulation results verify the performance of proposed algorithm in comparison with single layer video streaming.
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