適用於雲端架構下兼具高效能與平行化設計之分散式視訊編碼

High Efficient Distributed Video Coding with Parallelized Design for Cloud Computing

程瀚平(Han-Ping Cheng)

指導教授 ： 吳家麟

國立臺灣大學/電機資訊學院/資訊工程學研究所/碩士(2010年)

https://doi.org/10.6342/NTU.2010.00837

摘要

Wyner-Ziv (或簡稱WZ) 視訊編碼為分散式視訊編碼 (或簡稱DVC) 的一種實作，它基於Wyner-Ziv的理論，主要用來針對彼此間存在相關性的視訊資料進行失真壓縮。雖然近年來，許多能有效改進WZ視訊編碼壓縮效率的方法被提出，目前最先進的WZ編碼器，其壓縮效率跟目前最先進以預測移動為基礎的編碼器比較起來還是有段差距，尤其是在視訊內容移動較為複雜的情況下。除此之外，目前大部分提出的WZ編碼器，其解碼端的時間延遲都非常的長，這會阻礙WZ編碼器在即時系統上的實際應用。在這篇論文中，藉由結合近年來在轉換域WZ編碼器上所開發出的編碼技術，以及在編碼端與解碼端加入新的模組，一個實際且有效率的WZ視訊編碼器被提出，名為適用於雲端架構下兼具高效能與平行化設計之分散式視訊編碼 (或簡稱DISPAC) ，用來提昇WZ編碼的壓縮效率。不僅如此，DISPAC還擁有另一個獨一無二的特性，就是其解碼端所採用的模組非常適合平行化計算，這使得DISPAC的解碼速度能夠增快許多。在模擬雲端運算架構 (由許多多核心中央處理器與通用計算圖形處理器所組成) 的環境下實驗出來的結果顯示，與目前最先進的WZ編碼器相比，DISPAC編碼器可以提昇多達3.6分貝的壓縮效率以及多達61.1倍快的解碼速度。

關鍵字

分散式視訊編碼 ； Wyner-Ziv視訊編碼 ； 平行計算 ； 雲端運算 ； CUDA ； 多核心中央處理器 ； 通用計算圖形處理器 ； 區塊模式選擇 ； side information改進

並列摘要

Wyner-Ziv (WZ) video coding – a particular case of distributed video coding (DVC), is based on the Wyner-Ziv theorem for lossy coding of correlated video sources. Although some works, with improved performance, have been made in recent years, the coding efficiency of state-of-the-art WZ codecs is still far from that of the state-of-the-art prediction-based codecs, especially for high and complex motion contents. Moreover, most reported WZ codecs have a high time delay in the decoder, which hinders its practical application in real-time systems. In this work, by combining coding tools developed in recent literatures on transform domain WZ video coding with some newly developed modules on both encoding and decoding sides, an efficient and practical WZ video coding architecture, dubbed as DIStributed video coding with PArallelized design for Cloud computing (DISPAC), is proposed to better the rate-distortion (RD) performance. Another unique feature of DISPAC, lies in the parallelizability of the modules used by its WZ decoder which increased the decoding speed largely. Experimental results conducted on an emulated Could computing environment (consisting of multi-core CPU and GPGPU processors) reveal that DISPAC codec can gain up to 3.6 dB in the RD measures and 61.1 times faster in the decoding speed as compared with the-state-of-art WZ video codec, respectively.

並列關鍵字

Distributed video coding ； Wyner-Ziv video coding ； parallel computing ； Cloud computing ； CUDA ； multi-core CPU ； CPGPU ； block mode selection ； side information refinement

參考文獻

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