H.264可調式視訊編碼之空間層際移動估測快速演算法 摘要
由於視訊壓縮編碼、網路以及儲存能力的發展,使得多媒體系統的應用越來越普及與廣泛,因此,如何有效率的提供資訊給不同條件限制的使用者變得非常重要,可調式視訊的概念也就此誕生。 H.264可調式視訊編碼標準(SVC)是目前最新的可調式視訊編碼技術,它以H.264為核心,並加入了層際間預測的概念,大幅改善了以往視可調式訊編碼標準的缺點,儘管如此,運算複雜度太過龐大一直是SVC面臨的最大問題,特別在開啟層際間預測之空間可調架構下,增強層移動估測複雜度幾乎占了整體複雜度的90%以上。 有鑑於此,本論文利用了增強層兩種預測移動向量間的關係,以及增強層各模式間最佳移動估測方向的相關性,提出了一套應用在開啟層際間預測之空間可調架構下的移動估測快速演算法。實驗結果顯示,與原始JSVM 9.12全域搜尋相比,最多可節省67.4%的運算複雜度,而最多只犧牲不到0.05dB的視訊品質。 |
Fast Inter-Layer Motion Estimation
Algorithm on Spatial Scalability in H.264/AVC Scalable Extension Abstract
With
the improvements of video coding technology, network infrastructures, storage
capacity, and CPU computing capability, the applications of multimedia
systems become wider and more popular. Therefore, how to efficiently provide
video sequences to users under different constraints is very important, and
scalable video coding is one of the best solutions to this problem. H.264
scalable extension (SVC) that is constructed based on H.264/AVC is the most
recent scalable video coding standard. SVC utilizes the inter-layer
prediction to substantially improve the coding efficiency comparing with the
prior scalable video coding standards. Nevertheless, this technique results
in extremely large computation complexity which obstructs it from practical use. Especially on
spatial scalability, the complexity of the enhancement layer motion
estimation occupies above 90% of the total complexity. The main objective of
this work is to reduce the computation complexity while maintaining both the
video quality and the bit-rate. This thesis proposes a fast inter-layer
motion estimation algorithm on temporal and spatial scalabilities for SVC. We
utilize the relation between two motion vector predictors from the base layer
as well as the enhancement layer respectively and the correlation between all
the modes to reduce the number of search times. The simulation results show
that the proposed algorithm can save the computation complexity up to 67.4%
compared to JSVM9.12 with less than 0.0476dB video quality degradation. |