H.264 影像解碼之系統設計及硬體軟體整合平台｜國立中央大學博碩士論文系統

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研究生：	林宏龍 Hung-long Lin
論文名稱：	H.264 影像解碼之系統設計及硬體軟體整合平台 A System Level Design of H.264 video decoder with Hardware and Software Integration Platform
指導教授：	蔡宗漢 Tsung-Han Tsai
口試委員:
學位類別：	碩士 Master
系所名稱：	資訊電機學院 - 電機工程學系在職專班 Executive Master of Electrical Engineering
畢業學年度：	97
語文別：	中文
論文頁數：	92
中文關鍵詞：	解碼、嵌入式系統
外文關鍵詞：	H.264, decoder, embeed system
相關次數：	點閱：9 下載：0
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本碩士論文中，利用SOCLE CDK2007 平台實現了一個H.264/AVC 解碼器，經由複
雜度分析發現，除區塊濾波器為其中較佔據系統資源其中之一的模組，所以我們選擇使用
硬體實現以及搭配軟體處理其他部分，第6 章表格中有列出幾個架構效率比較，經過幾篇
論文中的效率比較，我們選擇了一個效率較佳的除區塊濾波電路來做硬體實現，此架構中
因為垂直濾波跟水平濾波做平行處理，此除區塊濾波電路利用幾組暫存器的搬移實現了平
行處理垂直以及水平濾波，另外本文在實現過程中也發現除區塊電路的平行處理上控制電
路做了修改之後可以比原先參考架構縮短了30%的時間去完成一張圖片的解碼。第6 章會
提到硬體修正前以及修正後的結果，並且將解碼的時間與多篇paper 做一個比較。
關於色差轉換部分由於其計算方式使用到浮點運算在最佳化初期占了整體效能的30%
所以也選擇以硬體實現。
軟體部分使用網路上的原始程式，搭配ARM 的profile 分析，針對其中各個模組個別
去做最佳化以及降低記憶體存取的頻率，使用內部暫存器去做各個區塊的運算。
在兩個硬體模組以硬體實現以後整合到系統整合版上之後必須考慮最佳化程序:
1. 系統周邊最佳化，本文中第6 章有提到我們針對實現H.264 播放影像針對的LCD 以及
外部記憶體SDRAM，加上系統PLL 控制以達成最佳化的目的。
2. 硬體效能量測，本文第6 章節提到硬體執行所需要的時間，根據RTL 模擬可以得到改
善後的結果。
3. 未來必須針對軟體且利用ARM 公司所提供的profile 軟體去預估軟體執行過程的最遲
緩的地方做演算法最佳化。
經過以上處理程序系統上撥放效能可以從QCIF 0.5fps，提升到10fps。

In this master thesis, this uses the platform of SOCLE CDK2007 to implement an
H.264/AVC decoder. Through the complexity of analysis of previous study, the De-block Filter
module should be one of the modules which occupy more system resource, so that we decide to
use hardware to implement this module. Chapter6 sets out a few forms to in the framework of
De-block efficiecy, after several in the efficiency of comparison, we have chosen a better
efficiency in a addition to De-block Filter circuits to do implementation. The Filter circuit in
addition to block the use of several 4x4 registers of the move between register to achieve the
parallel processing of the vertical and horzinortal Filtering. Also in the realization of the
implementation of this article, we found the parallel processing control circuit can be done to
amend the original frame De-block Filter time, which can reduce 30% the processing time of
De-block Filter than original architecture. Chpater 6 will be referred to the amendment and make
a Filtering time comparison to more paper.
For YUVtoRGB which occupy 30% system performance, so we decide to implement it by
Hardware.
In the software part of the use of ARM’s profile analysis, we found the conversion of YUV
to RGB also wasted 30% CPU time, so we will use hardware to implement the YUV to RGB
module.
After implementation of two hardware module, we must to consider optimize process before
hardware and software integrate into the system board:
1. The best system around, and in this article are referred to Chapter 6 players for the
realization of H.264 Video, we focus on LCD, external SDRAM and system PLL
optimization.
III
2. Hardware performance measurement, Chapter 6 of this article to the hardware section
execution time, according to the RTL simulation we can get the improved result.
3. In the future, we should use ARM’s profile software to estimate the software execution
process and find out the CPU execution cycles to improve the wasted CPU cycles by
software algorithm.
After performance enhancement which can improve QCIF 0.5fps to 10fps in H.264 system.

摘 要.................................................... I
Abstract................................................ II
誌謝.....................................................IV
目錄......................................................V
圖目錄.................................................VIII
第一章 緒論...............................................1
1.1 研究動機..............................................1
1.2 研究內容與目標........................................1
1.3 論文內容概述..........................................2
第二章 H.264/AVC 簡介.....................................3
2.1 H.264 壓縮標準簡介....................................3
2.1.1 網路提取層 (Network Abstraction Layer，NAL) ........4
視訊編碼層 (Video Coding Layer，VCL) .....................6
2.1.2 H.264/AVC 影像格式階層架構..........................6
2.1.3 編碼模式Slices......................................8
2.2 H.264/AVC 解碼器簡介..................................9
2.2.1 反轉換 ( Inverse Transform ).......................10
2.2.2 反量化 ( Inverse Quantization ) ...................11
2.2.3 框內預測 ( Intra Prediction) ......................12
2.2.3.1 Intra 4X4 mode prediction process for luma samples .................................................12
2.2.3.2 Intra 16X16 mode prediction process for luma samples .................................................14
2.2.3.3 Intra 8X8 mode prediction process for Chroma samples .................................................14
2.2.4 框間預測 ( Inter Prediction) ......................14
2.2.5 彈性區塊大小 ( Variable Block Sizes )..............15
2.2.6 精準度為四分之一像素的移動向量 ( Quarter Pixel Precision Motion Vector) ................................17
2.2.7 消除區塊濾波器 ( Deblocking Filter ) ..............19
2.2.7.1 濾波程序.........................................28
2.2.8 區塊濾波順序.......................................30
第三章 Hardware/Software Partition on H.264 Video Decoder..................................................32
第四章 Software-based Design.............................36
4.1.1 CDK2007............................................36
4.1.2 ARM 926EJS.........................................36
4.1.3 系統周邊簡介.......................................37
4.1.4 ARM 平台設計流程圖.................................40
第五章 硬體設計..........................................42
5.1.1 RTL 硬體方塊圖.....................................42
5.1.2 DEBLOCK RTL 硬體方塊圖.............................43
5.1.3 除區塊濾波資料序列示意圖...........................47
5.1.4 YUV to RGB RTL 硬體方塊圖..........................60
第六章 實驗結果與DEMO ...................................63
6.1.1 RTL Simulation 結果................................63
6.1.2 系統最佳化.........................................67
6.1.3 軟體最佳化.........................................69
6.1.4 System Integration Test Result.....................72
第七章 結論..............................................74
參考文獻.................................................76

                                

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