以內容特徵為基礎之運動向量估測演算法及架構研究

Abstract

動向量估測在視訊壓縮編碼上已經成為一關鍵性的重要技術， 其最主要的目的是消除相鄰畫面間在時間軸上的重複資訊， 以達到高壓縮比的目的，這樣的技術已經被廣泛的應用在各種視訊壓縮標準中， 但是在過去相關的研究中，不論是全域搜尋演算法或者是快速搜尋演算法， 皆未曾考慮視訊內容特徵的應用。 因此本論文以視訊內容特徵為基礎來探討其在運動向量估測中的應用。 本論文中共提出兩種的演算法及其架構， 一為兩階段式快速搜尋法則/架構， 二為電源知覺運動向量估測演算法/架構， 兩者都是利用每一影像區塊內容之不同而做不同之處理， 以達到降低運算量及電源知覺的目標。 後者更利用一簡單之控制機制以收斂最終的功率消耗，達到更佳的電源知覺效能。

兩階段式快速搜尋演算法中，利用每一區塊中高頻部份做低解析度量化處理， 並利用此一低解度量化後高頻資訊的特性決定搜尋掃描方向， 以有效的重複利用低解析度量化資料，然後再運用這些低解度量化高頻資訊做為比對的標準， 快速篩選出最有可能的位移向量供第二階段精確比對用。 第二階段則是利用一般全區域式區塊搜尋演算法常用的 SAD（sum of absolute） 比對標準，在第一階段所產出的可能位移向量中， 求出最佳的運動位移向量。這樣的作法可以大大降低整體的運算量， 並且在所提出的實現架構中，對於資料的存取， 亦能保持相當程度的重複運用以及規則存取特性， 最重要的是在運動向量補償品質上，僅犧牲些許的失真。

電源知覺能力之運動向量估測演算法/架構則是依據不同視訊內容特徵， 將依區塊內的資料區分為高頻資訊及低頻資訊，並且僅對低頻資訊作取樣處理， 再透過一控制機制達到保持整體取樣率於一定範圍， 由於取樣率在運動向量估測架構下等比於功率消耗， 因此在此一演算法下實現的架構， 在以電池為主電力來源的攜帶式視訊裝置上， 能依照電池特性做調整使之具備較佳之電源功耗（電池使用時間）, 同時維持較好的運動向量補償品質。

在最後的模擬結果，本論文所提出的以視訊內容特徵為基礎下， 不論是兩階段式快速搜尋演算法/架構或電源知覺能力之運動向量估測演算法/架構， 在可攜式多媒體的應用領域上，都能有較佳的電源及品質效能。

The major objective of this thesis is to apply content-based approaches for motion estimation algorithms and architectures. Motion Estimation (ME) has been proven to be effective to exploit the temporal redundancy of video sequences and, therefore, becomes a key component of many multimedia standards, such as MPEG-X and H.26X standards. In such multimedia systems, the motion estimation dominates huge computation load and tends to consume much power. This issue has become a significant problem. In order to solve this problem, to develop fast searching algorithms and power-aware architectures becomes a most important issue for such video systems, especially for a portable video device which is powered by battery. Although a great deal of effort has been made on this field, considering the content property of video source on the motion estimation application is still seems to be lacking. In this thesis, we adopted a content-base methodology to meet the requirement of fast searching ME and power-aware ME for such portable video devices. This thesis proposes a edge-driven two-phase ME algorithm based on the content of video sources to reduce computation load in the matching procedure and a content-based power-aware algorithm which adaptively subsamples the background pixels only to perform grace trade-offs between quality degradation and power consumption. By employing the content-based methodology, these proposed algorithms, either for fast searching algorithm or power-aware algorithm, can achieve better results than the non-content-based ones.

In the proposed two-phase motion estimation, to match the low resolution quantized edge pixels of a macro-block is used in the first phase. According to the edge pixels span, the algorithm makes decision of suitable search scan-direction to reuse the quantized data more efficiently. Then it generates the survived motion vectors for the second phase which employs the SAD as the error criteria to perform accurate matching. This content-driven algorithm can reduce the significant computational load comparing with the full-search algorithm and still be more efficient than the existed two-phase algorithm. The content-based power-aware algorithm performs power-aware function by disable/enable processing elements according to the subsample mask based on the content of the video sources. The power-aware approach extracts the edge pixels of a macro-block and subsamples the non-edge pixels only to maintain the quality performance in acceptable level. Since the power consumption is proportional to the subsample rate, this content-based algorithm adopts a close-loop control mechanism to avoid the diverse problem of subsample rate in various video sources and hence keep the subsample rate in stationary state. Founded on the proposed content-based algorithm, the power-aware architecture can dynamically operate at different power consumption modes with little quality degradation only according to the remaining capacity of battery pack to achieve better battery discharging property.

Motivating from the applications of content methodology, this thesis proposes a fast algorithm and a power-aware algorithm to implement the corresponding architectures for conquering the drawbacks without employing content-based technique for the portable multimedia devices. As the simulation results showed, the proposed content-based ME algorithms and architectures can achieve better power and quality performance for the portable multimedia applications than those without adopting the content-based methodology.