本文關鍵詞： HEVC CUDA 并行算法 幀內(nèi)預測　出處：《大連理工大學》2015年碩士論文　論文類型：學位論文

【摘要】：隨著人們對視頻質量要求的不斷提高,在H.264/AVC視頻編碼標準之后于2013年,國際視頻編碼專家組VCEG和動態(tài)圖像專家組MPEG聯(lián)合推出了最新的高性能視頻編碼標準HEVC, HEVC的目標是比H.264節(jié)省大約50%的碼率。HEVC編碼性能的提高是以計算復雜度大幅度增加為代價的,為了更廣泛的應用HEVC,有必要提高編碼速度,于是如何提高HEVC編碼效率成為了研究熱點。目前大多數(shù)計算機中最主要的兩種處理器分別是多核CPU和眾核GPU, GPU擁有大量的運算單元,適用于通用并行計算。NVIDIA公司推出的計算機統(tǒng)一設備架構——CUDA為GPU編程提供了很好的平臺。本文基于HEVC標準算法,針對幀內(nèi)預測中的關鍵技術,設計相應的并行算法,并基于CUDA進行實現(xiàn)。文中首先分析數(shù)據(jù)之間的相關性,然后針對亮度分量和色度分量幀內(nèi)預測求取預測值設計不同的并行算法；針對整數(shù)DCT變換和反變換,基于蝶形快速算法設計并行算法；針對量化和反量化設計并行算法；針對幀內(nèi)預測并行算法進行優(yōu)化。另外,本文設計了一種逐步縮小模式搜索范圍的幀內(nèi)預測快速算法,在預測精度損失較小的條件下將其計算量減小一半以上。針對快速算法設計了并行算法,并基十CUDA實現(xiàn)。本文對設計的各個并行算法均在CPU+GPU異構平臺上采用CUDA語言進行編程實現(xiàn),并使用高清視頻序列進行了大量實驗。實驗表明,本文的幀內(nèi)預測并行算法相比于原始算法在保證圖像質量的前提下,加速比可達5.6倍；快速幀內(nèi)預測并行算法相比于原始算法在基本不改變圖像質量的前提下,加速比可達8.5倍。
[Abstract]:In 2013, after the H.264 / AVC video coding standard, with increasing demand for video quality, The international video coding expert group VCEG and the dynamic image expert group MPEG jointly launched the latest high-performance video coding standard HEVC. The goal of HEVC is to save about 50% bit rate compared with H.264. The improvement of the performance of HEVC coding is at the cost of a significant increase in computational complexity. In order to apply HEVC more widely, it is necessary to improve the coding speed, so how to improve the efficiency of HEVC coding has become a research hotspot. At present, the two main processors in most computers are multi-core CPU and multi-core GPU, and GPU has a large number of computing units. The computer unified device architecture, which is suitable for general parallel computing. NVIDIA, provides a good platform for GPU programming. Based on the HEVC standard algorithm, this paper designs the corresponding parallel algorithm for the key technology of intra prediction. In this paper, we first analyze the correlation between data, then design different parallel algorithms for intra prediction of luminance component and chrominance component, and design different parallel algorithms for integer DCT transform and inverse transform. Design parallel algorithm based on butterfly fast algorithm; design parallel algorithm for quantization and inverse quantization; optimize parallel algorithm for intra prediction. In addition, this paper designs a fast algorithm of intra prediction which gradually reduces the scope of pattern search. The computational complexity is reduced by more than half under the condition that the loss of prediction precision is small. A parallel algorithm is designed for the fast algorithm. In this paper, all parallel algorithms are programmed on the CPU GPU heterogeneous platform with CUDA language, and a large number of experiments are carried out using high-definition video sequences. Compared with the original algorithm, the in-frame prediction parallel algorithm in this paper has a speedup of 5.6 times on the premise of guaranteeing image quality, and compared with the original algorithm, the fast intra prediction parallel algorithm does not change the image quality. The acceleration ratio can reach 8.5 times.
【學位授予單位】：大連理工大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TN919.81

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相關碩士學位論文 前1條

1 吳羨;H.264編碼關鍵模塊并行算法設計及其在CUDA上的實現(xiàn)[D];大連理工大學;2014年

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本文編號：1519178