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研究生：	盧泯龍 Lu, Min-Long
論文名稱：	HEVC框內Coding Unit深度決策之快速演算法 Fast Coding Unit Depth Decision Algorithm for HEVC Intra Prediction
指導教授：	賴源泰 Lai, Yen-Tai
學位類別：	碩士 Master
系所名稱：	電機資訊學院 - 電機工程學系 Department of Electrical Engineering
論文出版年：	2013
畢業學年度：	101
語文別：	英文
論文頁數：	108
中文關鍵詞：	HEVC 、框內預測、分割編碼單元、候選模式
外文關鍵詞：	HEVC, intra prediction, coding unit partition, candidate modes
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HEVC 是 H.264之後被提出的最新一代影像壓縮標準。之所以被取名為HEVC的原因是其目標致力於高編碼效率與高影像品質。隨著HEVC的發展，HEVC編碼所花費的時間還是比先前的H.264多了許多。HEVC框內預測所使用的預測模式已被大幅增加至35個，其中包含33個角度預測模式，DC模式和planar模式。在HEVC中，一張圖會先被切割成許多同一尺寸的最大編碼單，而每一個最大編碼單元會再被切割成不同尺寸的編碼單元。編碼單元的切割會組成四分樹架構。RDO有權力決定如何去切割每一個編碼單元。
因為HEVC必須藉由計算RDO來決定編碼單元的切割，所以 RDO的計算量佔了絕大部分的編碼時間。為了減少RDO的計算量，此篇論文提出直接決定編碼單元切割至8×8編碼單元，合併編碼單元決定每個最大編碼單元的最佳編碼單元尺寸和找出每個編碼單元之候選模式。因此能減少不必要的RDO計算。本篇所提出的演算法在框內預測的編碼時間可平均減少51%，而只有少量的PSNR損失與位元率升高。

High Efficiency Video Coding (HEVC) is a new generation of video coding, which was the successor of H.264/AVC. The name HEVC was given for the consideration of high quality and high efficiency. As the development of HEVC began, HEVC still required more coding time than H.264/AVC. The modes of HEVC intra prediction had been increased to 35 modes with 33 angular modes, DC mode and planar mode. In HEVC, a frame is divided to Largest Coding Unit (LCU) with uniform size, each LCU will be divided into several Coding Unit (CU) with various size. The coding unit partition will form a quad-tree structure. RDO of each coding unit will have the authority to made decision for coding unit partition.
Since HEVC needs to calculate a lot of RDO during coding unit partition, the calculation of RDO will consume a lot of coding time. In order to reduce the calculation of RDO, the proposed algorithm will perform a direct coding unit partition into coding unit with size 8×8 and coding unit merging to decide the best coding unit size in each LCU. Beside the direct coding unit partition and coding unit merging, proposed algorithm will also find the candidate modes for each coding unit depending on the size of coding unit. By finding the candidate modes of each coding unit, the calculation of unnecessary RDO will be reduced. The performance of proposed algorithm was capable to speed up the coding time of intra prediction averagely 51% with negligible PSNR loss and slight bitrate increase.

ABSTRACT 
ACKNOWLEDGMENT 
CONTENTS 
LIST OF TABLES 
LIST OF FIGURES 

Chapter 1
Introduction	1
1 Research Background	1
2 Motivation	5
3 Thesis Organization	6

Chapter 2
Concept of H.265/HEVC	7
1 Overview of H.265/HEVC	7
1.1 Prediction Unit of H.265/HEVC	14
1.2 Coding Unit of H.265/HEVC	15
1.3 Largest Coding Unit of H.265/HEVC	16
1.4 Transform Unit of H.265/HEVC	17
1.5 Transform and Quantization	18
1.6 Entropy Coding	21
5.2 Slice and Slice Groups	24
2 Inter Prediction for H.265/HEVC	25
2.1 Motion Vector Prediction	26
2.2 Advanced Motion Vector Prediction (AMVP)	27
2.3 Multiple Reference Frame	28
2.4 Motion Compensation	29
3 Intra Prediction for H.265/HEVC	29
3.1 Intra Mode Prediction	31
3.2 Coding Unit Block Size for Intra	34
3.3 Prediction Unit of Intra Prediction	34
4 Residual Quad-tree	35
4.1 Residual Quad-tree for Inter Prediction	37
4.2 Residual Quad-tree for Intra Prediction	38
5 Deblocking Filter	39
6 Sample Adaptive Offset Filter (SAO)	41
6.1 Band Offset (BO)	42
6.2 Edge Offset (EO)	43
7 Adaptive Loop Filter	44

Chapter 3
Proposed Algorithm	46
1 Overview of the Proposed Algorithm	46
2 Related Works	51
3 Proposed Algorithm	54
3.1 The Proposed Order of Intra Prediction Order	58
3.2 Coding Unit Splitting to 8×8	60
3.3 Best Mode for each 8×8 Coding Unit based on Candidate Modes	61
3.4 Final Coding Unit Size	63

Chapter 4
Experimental Results	70
1 Overview of Experimental Results	70
2 Experimental Configuration	70
3 Measuring Criteria	73
3.1 Peak Signal-to-Noise Ratio	74
3.2 Bitrate	74
3.3 Calculation Equation	74
4 Experimental Results	76
4.1 Coding Performance of HM10.1	76
4.2 Coding Performance of Proposed Algorithm	80
4.2.1 BlowingBubbles	80
4.2.2 BQSquare	83
4.2.3 RaceHorses	86
4.2.4 BasketBallDrill	89
4.2.5 FourPeople	92
4.2.6 Johnny	95
4.2.7 Kimono	98
4.2.8 ParkScene	101

Chapter 5
Conclusion	105
References 106

                                    

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校內：2023-12-31公開
校外：不公開電子論文尚未授權公開，紙本請查館藏目錄

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