标题: | 针对可调视讯编码粗略可调性之模式相依的位元与失真解析模型 Analytical Mode-Dependent Rate and Distortion Models for H.264/SVC Coarse Grain Scalability |
作者: | 曾于真 Tseng, Yu-Chen 彭文孝 Peng, Wen-Hsiao 多媒体工程研究所 |
关键字: | 位元与失真模型;mode-dependent;rate and distortion models |
公开日期: | 2011 |
摘要: | 可调视讯编码的层间预测和动作补偿预测中执行动作预测的区块其不同的分割模式会导致位元与失真上差异。然而现今只有少数模型可以解释可调式视讯编码位元与失真行为,更遑论有任何方法可以让我们针对可调视讯编码中不同的区块分割模式分析其位元与失真关系。针对可调视讯编码粗略可调性,本论文推导出了一个解析性及模式相依的位元与失真关系模型。考虑到加强层为可采用层间残留预测的压缩方式,我们对可调视讯编码中基础层与加强层各提供了一取决于区块分割模式和影像特性的位元与失真模型。在我们所提出的位元与失真模型推演过程中采纳了一个向前信道模型以及一个时间上稳态的过程假设,我们藉由一个动作预测轨迹诠释重建区块,并且将残留变异数设计成一个统计量模型。实验结果显示,我们提出的模型可以很准确的估量出不同区块分割模式,其真实压缩出的基础层及加强层的位元与失真曲线。并且最后针对不同区块分割层间残留预测的效能分析后,所提出的模型也呈现与真时压缩相似的位元与失真趋势。 In Scalable Video Coding (SVC), the inter-layer prediction and the variable motion estimation block partition modes for motion-compensated prediction (MCP) cause differences in rate and distortion behavior; however, there are just few models could explain the rate and distortion behavior of SVC, not to mention methods which focus on analyzing the rate and distortion of different partition mode pairs in SVC. In this thesis, we derive analytical mode-dependent rate and distortion models for Coarse-grain scalable video coding techniques. The rate and distortion models for base and enhancement layer both depend on the partition mode and sequence characteristics with consideration of the inter-layer residual prediction capability in enhancement layer. Adopting a forward channel model and an assumption of temporal-stationary process in the derivation of proposed models, we interpret the reconstructed block by a motion prediction trajectory and model the transformed residual variance into a mode-dependent statistic. Our experimental results show that the proposed model can estimate the actual-coded R-D curves of different partition modes in base layer and enhancement layer with high accuracy. In addition, similar tendencies between model and actual-coded curve are observed over the performances of different mode pair encoded with inter-layer residual prediction. |
URI: | http://140.113.39.130/cdrfb3/record/nctu/#GT079857553 http://hdl.handle.net/11536/48477 |
显示于类别: | Thesis |
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