適用於H.264/MPEG4-AVC及其可調式視訊編碼之移動估測設計

Abstract

移動估測在視訊編碼的過程中，具有非常高的複雜度，因此成為即時影像編碼的瓶頸，在高壓縮律規格(H.264/AVC)的可調式視訊編碼中，由於其額外引用的層間預測編碼，使得原本整數點移動估計之高頻寬存取所帶來的問題更加嚴重。因此，本論文引用一能有效改善層間預測高頻寬存取的演算法並提出相對應的硬體架構，此硬體架構使得整數點移動估測和層間預測能併行運算並共用運算時所需的資料。此外，為了改善分數點移動估測的高複雜度和高計算量，本論文引用了一分數點快速演算法並提出相對應的硬體架構，此提出之架構與先前架構相比運算速度可增加三倍。由於多種移動向量和來自於層間預測的多種編碼方式，使得分數點移動估測的運算量和運算時間大為增加，為了更進一步減少分數點移動估測的運算時間和運算量，本論文引用了一能有效篩選欲執行分數點移動估測的編碼方式之演算法，並且將其延伸與多層解析度移動估測演算法之結果一併考慮，進而提出一種能從不同層解析度編碼方式之中有效篩選欲執行分數點移動估測的編碼方式之演算法，經過此演算法，相較於原先的最多20種編碼方式，此演算法篩選至僅僅3種編碼方式須要被執行分數點移動估測，此演算法相較於先前無篩選的做法訊雜比下降了0.106dB而位元率增加了3.542%。

Motion estimation is (ME) is the most complex part and the bottle neck of a real time video encoder. The adoption of inter-layer prediction (IL prediction) in H.264/AVC SVC extension even increases the computing time and memory bandwidth of ME. Thus, we adopted the previous data efficient inter-layer prediction algorithm [4] to save the memory bandwidth. In this thesis, we propose the corresponding hardware architecture for inter-layer prediction which can process INTER mode and different inter-layer prediction modes in parallel to save the computing time and memory bandwidth. Furthermore, in order to reduce the high complexity and computation of FME, we adopt the Single-Pass Fractional Motion Estimation (SPFME) as our fast FME algorithm in our FME process. We then propose the corresponding FME hardware architecture for SPFME according to the previous architecture of FME design [3]. Compared with the previous architecture, our proposed architecture can speed up to four times faster. There are many prediction modes due to the adoption of inter-layer prediction and different block types. Thus, to further reduce the complexity and computing time of FME, we adopt the pre-selection algorithm of Li’s to eliminate some prediction modes from FME process. However, the Parallel Multi-Resolution Motion Estimation (PMRME) algorithm [1] is adopted in our IME process. Hence, we further propose a multi-level mode filtering scheme to select 3 prediction modes from 3 different search levels. Finally, we integrate the adopted IL prediction, mode filtering, and the SPFME algorithm. The simulation results shows that the proposed function flow with mode filtering can achieve average 3.542% of bit-rate increment and 0.106dB of PSNR degradation in CIF sequence for 2 spatial layers. The implementation results of the whole ME architecture is also shown. It can support CIF+480p+1080p video @60 fps under 135MHz.