臺灣博碩士論文加值系統

移動估計演算法的高計算複雜度與資料頻寬存取量，一直以來是視訊編碼研究領域中非常重要的研究議題。然而，隨著高解析度視訊影像應用需求的增加，使得移動估計演算法的高資料頻寬存取量，成為影響整體視訊編解碼器效能的重要關鍵。此外，為了達到應用可調性，可調式視訊編碼所採用的層間預測模式，亦為移動估計帶來更高之資料頻寬存取量及計算複雜度。為了解決視訊編碼之高資料頻寬存取量所造成編碼系統效能下降之問題，本論文提出若干適用於整數點及分數點移動估計演算法之資料存取及計算量減少演算法。
針對整數點移動估計資料頻寬之問題，本論文提出一位元失真率最佳化的頻寬有效率之移動估計演算法。在此演算法中，本論文提出一數學模型以描述位元失真率與頻寬之關係。藉由此模型的建立，進而發展出一低頻寬需求之移動估計演算法。此外，經由此數學模型的幫助，本論文亦發展出一頻寬感知移動估計演算法。此演算法可以在頻寬有限的條件之下，適當的分配頻寬資源給移動估計演算法，進而達到更佳的失真位元率表現。透過本論文所發展之方法，可以達到78.82%頻寬節省。
在可調式視訊編碼中，由於其額外採用的層間預測方式，使得原本整數點移動估計之高頻寬存取所帶來的問題更加嚴重。因此，本論文提出若干個適用於可調式視訊編碼之高效頻寬層間預測移動估計演算法。透過利用畫面層間之高相關性，達到較高的資料共用性進而減少多餘的資料存取。實驗結果顯示，本論文提出之適用於可調式視訊編碼之高效頻寬層間預測演算法，可至少達到50.55%的資料頻寬之節省。
除了可調式視訊編碼中額外採用的層間預測方法所帶的高資料頻寬存取量之問題外，分數型移動估計演算法的高計算複雜度，亦大幅度的造成計算複雜度的增加進而影響可調式視訊編碼器的系統效率。因此，本論文提出一分數型移動估計模式預先選擇演算法，以預先過濾掉潛在可忽略之預測模式。藉由觀察不同模式之整數型移動估計成本及分數型移動估計成本之間之關係，進而提出若干個模式過濾機制。透過本論文提出之演算法，在不造成太多位元失真率效能失真的情況之下，平均可達到65.97%模式減少。
對於分數型移動估計演算法因硬體設計考量，導致參考資料未被從外部記憶體下載進來所造成的效能下降而言，本論文提出了搜尋範圍重新決定演算法用以減少視訊編碼器之效能下降。在此演算法中，本論文透過觀察移動向量子與非重疊區域尺寸之關係，提出一數學公式予以描述。因此，透過移動向量子的大小，即可計算出非重疊區域尺寸，進而重新計算所需之搜尋範圍尺寸。此外，本論文亦提出一搜尋範圍長寬比決定演算法，透過移動向量子與非重疊區域尺寸關係之數學求解，可得到較佳之非對稱式搜尋範圍長寬比。經由本論文所提出之搜尋範圍與長寬比決定之演算法，可達到90%的位元率下降改善。
整體而言，透過本論文所提之演算法，除了可大幅度的減少資料頻寬之存取外，亦可減少整數及分數點的計算複雜度，進而達到更佳視訊編碼效能之改善。

In the video coding system, the overall system performance is dominated by the motion estimation module due to its high computational complexity and memory bandwidth intensive data accesses. Furthermore, with the increasing demands of high definition TV, the system performance drop caused by the intensive data bandwidth access requirement becomes even more significant. In addition, the additional adopted Inter-layer prediction modes of scalable video coding also significant increase the data access bandwidth overhead and computational complexity.　To solve the high computation complexity and intensive data bandwidth access problems, this dissertation proposes several data access bandwidth and computational complexity reduction algorithms for both of integer and fractional motion estimation.
First, this dissertation proposes a rate distortion bandwidth efficient motion estimation algorithm to reduce the data bandwidth requirements in integer motion estimation. In this algorithm, a mathematical model is proposed to describe the relationship between rate distortion cost and data bandwidth. Through the modeling results, a data bandwidth efficient motion estimation algorithm is thus proposed. In addition, a bandwidth aware motion estimation algorithm based on the modeling results is also proposed to efficiently allocate the data bandwidth for motion estimation under the available bandwidth constraint. Simulation results show that our proposed algorithm can achieve 78.82% data bandwidth saving.
In scalable video coding standard, the additional included Inter-layer prediction modes significantly deteriorate the video system coding performance since much more data have to be accessed for the prediction purpose. Therefore, this dissertation proposes several data efficient Inter-layer prediction algorithms to lighten the intensive data bandwidth requirement problem in scalable video coding. By observing the relationship between spatial layers, several data reusing algorithms have been proposed and thus achieve more data bandwidth requirement reduction. Simulation results demonstrate that our proposed algorithm can achieve 50.55% data bandwidth reduction at least.
In addition to the system performance degradation caused by intensive data bandwidth access problem, the high computational complexity of fractional motion estimation also noticeably increases the system performance drop in scalable video coding. Therefore, this dissertation proposes a mode pre-selection algorithm for fractional motion estimation in scalable video coding. In our proposed algorithm, the rate distortion cost relationship between different prediction modes are observed and analyzed first. Based on the observing and analytical results, several mode pre-selection rules are proposed to filter out the potentially skippable prediction modes. Simulation results provide that our proposed mode pre-selection algorithm can reduce 65.97% prediction modes with ignorable rate distortion performance degradation.
Finally, for the video coding system performance drop problem caused by the fractional motion estimation process skipping due to hardware implementation consideration, this dissertation proposes a search range adjust algorithm to adjust the search range for the motion estimation so that the new decided search range can cover the absent reference data as much as possible for fractional motion estimation. By mathematically modeling the relationship between motion vector predictor and non-overlapping area size, the new search range can thus be adjusted. In addition, a search range aspect ratio adjust algorithm is also proposed in this dissertation by means of solving the mathematical equations. Through the proposed search range adjust algorithm, up to 90.56% of bitrate increasing can be reduced when compared to fractional motion estimation skipping mechanism. Furthermore, the proposed search range aspect ratio adjust algorithm can achieve better rate distortion performance when compared to the exhaustive search method under the same search range area constraint.
In summary, through the algorithms proposed in this dissertation, not only the data access bandwidth but the computational complexity of integer and fractional motion estimation can be reduced and thus improve the overall video coding system performance significantly.

摘　　要 iii
ABSTRACT v
Outline viii
List of Tables xi
List of Figures xiii
Chapter 1 Introduction 1
1.1. Introduction 2
1.2. Introduction of H.264/AVC 3
1.3. Introduction of H.264/AVC Scalable Extension (SVC) 5
1.4. Analysis for H.264/AVC and Its Scalable Extension 7
1.4.1 Computational Complexity Analysis for H.264/AVC 8
1.4.2 Memory Access Requirement Analysis for H.264/AVC 9
1.4.3 Memory Access Requirement Analysis for SVC 9
1.4.4 Problem Statement 10
1.5. Organization of this Dissertation 12
Chapter 2 RD Bandwidth Efficient Motion Estimation and Its Hardware Design with On-Demand Data Access 13
2.1. Introduction 14
2.2. Data Bandwidth Modeling for ME 16
2.2.1. Search Algorithms and Its Memory Bandwidth Modeling 16
2.2.2. Nearest Neighbours Search Algorithm and Its Bandwidth Modeling 17
2.3. Proposed Framework 19
2.3.1. RD Bandwidth Modeling for Video Contents and Search Steps 19
2.3.2. Proposed Bandwidth Aware ME Algorithm 22
2.4. Simulation Results 27
2.5. Proposed Architecture 34
2.5.1. Bandwidth Modeling Module Design 35
2.5.2. Design of the On-demand Reference Buffer 36
2.5.3. Timing Analysis with DRAM Access Latency 39
2.5.4. Implementation Results 41
2.6. Summary 42
Chapter 3 Data and Computation Efficient Inter Predictor Design for H.264/AVC Scalable Extension 44
3.1. Introduction 45
3.1.1. Introduction to Inter-Layer Prediction Modes in H.264/AVC Scalable Extension 46
3.1.2. Problem Description 49
3.1.3. Introduction to Bandwidth Efficient Motion Estimation Algorithms 51
3.1.4. Organization of this Chapter 52
3.2. Inter and Inter-Layer Residual Prediction Data Reuse Method 52
3.2.1. Matching Criteria of Different Prediction Modes 53
3.2.2. Proposed Data Reuse Method 55
3.2.3. Results 56
3.3. Low Bandwidth Inter and Inter-Layer Motion Prediction Algorithm 57
3.3.1. Analysis for Motion Vector Predictors 58
3.3.2. Proposed Low Bandwidth Data Reuse Method for Inter-Layer Motion Prediction 62
3.4. Data Efficient InterBL Prediction Algorithm 64
3.4.1. Analysis for Motion Vector Predictor and Motion Vector 65
3.4.2. Proposed Data Efficient InterBL Data Reuse Prediction Algorithm 67
3.5. Combination of All Low Bandwidth Inter-Layer Prediction Algorithms 68
3.5.1. Discussion of Data Bandwidth Reduction for Inter Prediction Mode 69
3.5.2. Algorithms Combination 70
3.6. Simulation Results 73
3.7. Summary 79
Chapter 4 An Efficient Mode Pre-Selection Algorithm for Fractional Motion Estimation in H.264/AVC Scalable Video Extension 80
4.1. Introduction 81
4.2. Analysis of Rate Distortion Cost between Prediction Modes 86
4.2.1. Observing the RDCost Relationship between Different Prediction Modes 86
4.2.2. Statistical Results 102
4.3. Proposed FME Mode Pre-selection Algorithm 104
4.4. Simulation Results 110
4.5. Hardware Architecture Design 112
4.6. Summary 116
Chapter 5 Rate Distortion Oriented Search Range Adjustment for Motion Estimation Hardware Design 117
5.1. Introduction 118
5.2. Analysis for MVP and Non-overlapping Area Size 121
5.3. Proposed Search Range and Aspect Ratio Adjust Algorithm 126
5.3.1. Search Range Adjust Algorithm 126
5.3.2. Search Range Aspect Ratio Adjust Algorithm 128
5.4. Simulation Results 132
5.4.1. Simulation Results of Search Range Adjust Algorithm 132
5.4.2. Simulation Results of Search Range Aspect Ratio Adjust Algorithm 137
5.5. Integration of All Proposed Search Range Adjust Algorithms 140
5.6. Summary 143
Chapter 6 Conclusions and Future Works 145
6.1. Conclusions 146
6.2. Future Works 148

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