HEVC幀間快速編碼算法的研究
發(fā)布時(shí)間:2017-12-31 16:22
本文關(guān)鍵詞:HEVC幀間快速編碼算法的研究 出處:《電子科技大學(xué)》2016年碩士論文 論文類型:學(xué)位論文
更多相關(guān)文章: HEVC 幀間預(yù)測 塊劃分 模式判決 殘差信息
【摘要】:隨著高清視頻應(yīng)用的快速發(fā)展,視頻傳輸和儲(chǔ)存方面產(chǎn)生了巨大的挑戰(zhàn)。在這一新環(huán)境下,Joint Collaborative Team on Video Coding(JCT-VC)工作小組制定了新的視頻編碼標(biāo)準(zhǔn)High Efficiency Video Coding(HEVC/H.265)來應(yīng)對(duì)挑戰(zhàn)。HEVC為了達(dá)到高效編碼的目的,在原有視頻編碼標(biāo)準(zhǔn)Advanced Video Coding(AVC/H.264)的基礎(chǔ)上增加了許多更加先進(jìn)的視頻編碼技術(shù),如靈活塊劃分方式、非對(duì)稱運(yùn)動(dòng)模式劃分、多預(yù)測塊模式。與H.264相比,HEVC在獲得相同視頻質(zhì)量的前提下可以降低50%左右的傳輸比特流,但在編碼復(fù)雜度計(jì)算量上也大大地增加。在計(jì)算能力一般的無線移動(dòng)終端設(shè)備上,由于設(shè)備不能支持所有編碼技術(shù)的使用,這勢必會(huì)大大降低編碼效率,從而無法突顯HEVC編碼效率上的優(yōu)勢。在視頻編碼技術(shù)中預(yù)測編碼是計(jì)算比重最大的一部分,而其中的幀間預(yù)測編碼又是重要的環(huán)節(jié)之一。因此,HEVC幀間快速編碼算法研究是當(dāng)今視頻編碼領(lǐng)域中非常重要的研究內(nèi)容之一。本文首先簡單地介紹了視頻編碼標(biāo)準(zhǔn)的發(fā)展歷程和視頻編碼的整體框架,然后對(duì)當(dāng)今國內(nèi)外在HEVC的快速編碼的研究做了系統(tǒng)的總結(jié)。接著,對(duì)HEVC的編解碼框架和相關(guān)關(guān)鍵技術(shù)作了簡要介紹。最后,針對(duì)HEVC幀間CU(Coding Unit)塊劃分和PU(Prediction Unit)預(yù)測模式做了詳細(xì)說明和深入研究。在針對(duì)HEVC的CU塊的劃分過程中,本文先參考空域上的鄰近LCU(Largest Coding Unit)的最大劃分深度(Depth)為當(dāng)前LCU劃定一個(gè)范圍,從而跳過部分深度下的PU預(yù)測模式判決過程,有效的降低編碼復(fù)雜度。為了進(jìn)一步降低CU劃分的計(jì)算復(fù)雜度,在每個(gè)深度進(jìn)行完P(guān)U模式預(yù)測判決之后,根據(jù)最佳模式下的殘差信息以及變換量化系數(shù)矩陣提出了提前結(jié)束CU劃分的算法。在針對(duì)HEVC幀間PU預(yù)測模式判決過程中,本文提出了針對(duì)編碼過程中占比最大的兩種PU模式——Skip模式和2Nx2N模式的快速算法。為了提前預(yù)測Skip模式,本文將Skip模式放在PU預(yù)測流程的最前面進(jìn)行。其中,快速Skip算法是通過挖掘殘差信息、變換量化系數(shù)以及量化參數(shù)與Skip模式之間的關(guān)系提出的?焖2Nx2N算法是通過分析編碼過程中產(chǎn)生的運(yùn)動(dòng)矢量殘差、變換量化系數(shù)中非零數(shù)目以及變換單元(Tranform Unit,TU)劃分的深度等編碼信息與2Nx2N模式之間的關(guān)系提出的。實(shí)驗(yàn)表明,兩個(gè)快速模式判決算法都取得了很好的編碼效果。同時(shí),由于兩個(gè)算法針對(duì)的是兩種不同的PU模式,因此可以將兩個(gè)算法合并使用。在兩個(gè)算法合并使用情況下,編碼時(shí)間在視頻質(zhì)量基本保持不變的基礎(chǔ)上在低延時(shí)場景下可以減少44%和在隨機(jī)插入場景下可以減少51%。本文提出的算法通過很好的利用編碼過程的已有的編碼信息和圖像視頻自身殘差相結(jié)合的方法,對(duì)幀間CU塊劃分和PU預(yù)測模式的判決提前做出了比較準(zhǔn)確的判斷,相當(dāng)程度上加快了HEVC編碼器的速度。因此,該算法對(duì)HEVC在今后實(shí)時(shí)系統(tǒng)中的應(yīng)用具有一定的參考價(jià)值。
[Abstract]:With the rapid development of high-definition video applications, produced a huge challenge for video transmission and storage. In this new environment, Joint Collaborative Team on Video Coding (JCT-VC) working group to develop a new video encoding standard High Efficiency Video Coding (HEVC/ H.265.HEVC) to deal with the challenges in order to achieve efficient encoding purpose in the original video encoding standard Advanced Video Coding (AVC/H.264) based on the increase in many more advanced video encoding technology, such as flexible partition, partition the asymmetric motion mode, multi block mode prediction. Compared with H.264, HEVC in the premise to obtain the same video quality can reduce about 50% of the bit stream, but in the encoding complexity of computation is greatly increased. In the wireless mobile terminal equipment general computing power, due to the use of equipment can not support all coding technology, This will greatly reduce the encoding efficiency, thus unable to highlight the HEVC advantage of encoding efficiency. In the video encoding technology in prediction encoding is the calculation part of the largest proportion, of which the interframe prediction encoding is one of the important aspects. Therefore, research on fast encoding algorithms for HEVC frames is one of the most important research contents in today's video encoding in the field. This paper briefly introduces the overall framework and the development of video encoding video encoding standard, and then study the fast encoding of today's HEVC at home and abroad to do a systematic summary. Then, the HEVC codec framework and related key technologies are briefly introduced. Finally, according to the HEVC frame CU (Coding Unit) and PU (Prediction Unit partition) in detail and in-depth study of prediction model for HEVC. In the CU block division process, with the reference of adjacent airspace on L CU (Largest Coding Unit) the maximum depth classification (Depth) for the current LCU delimit a range, thus skipping the PU depth prediction mode decision process, effectively reduce the encoding complexity. In order to further reduce the computational complexity of the CU division, after each depth after PU mode prediction decision, based on the best model the residual information and transform quantization coefficient matrix is proposed ahead of the end of CU division algorithm. For the HEVC PU inter frame prediction mode decision process, this paper presents a fast algorithm for PU model rather than the two biggest - Skip mode and 2Nx2N mode encoding process. In order to predict Skip model, this paper will be the most in front of the Skip mode on the PU in the forecast process. Among them, the fast Skip algorithm is proposed by mining the residual information, the relationship between the transformation and quantization coefficient and the quantization parameter and the model of Skip. Fast 2Nx2N algorithm by analyzing the motion vector residuals generated in the process of encoding, and the number of non-zero transform unit transform quantization coefficient (Tranform Unit TU) proposed the relationship between the depth of encoding information and 2Nx2N modes of the final method. Experimental results show that the two models are found quickly achieved good encoding effect at the same time, because the two algorithms are aimed at two different modes of PU, so it can be used in combination. The two algorithms in the two algorithms combined with case, the encoding time remain unchanged on the basis of the low latency scenarios can be reduced by 44% and can reduce the 51%. algorithm proposed in this paper by good the use of the existing information encoding process of encoding video and image combination in its residual random insertion scene in the video quality, for the inter CU partition and PU prediction mode decision made earlier than A more accurate judgement has speeded up the speed of HEVC encoder to some extent. Therefore, the algorithm has certain reference value for HEVC application in the future real-time system.
【學(xué)位授予單位】:電子科技大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2016
【分類號(hào)】:TN919.81
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