COMPUTATIONALLY EFFICIENT BASIC UNIT RATE CONTROL FOR H.264/AVC Thesis Submitted to The School of Engineering of the UNIVERSITY OF DAYTON In Partial Fulfillment of the Requirements for The Degree of Master of Science in Electrical and Computer Engineering By Tanner Ryan Adams UNIVERSITY OF DAYTON Dayton, Ohio December, 2013 COMPUTATIONALLY EFFICIENT BASIC UNIT RATE CONTROL FOR H.264/AVC Name: Adams, Tanner Ryan APPROVED BY: Eric J. Balster, Ph.D. Frank A. Scarpino, Ph.D. Advisor Committee Chairman Committee Member Assistant Professor, Department of Professor Emeritus, Department of Computer and Electrical Engineering Computer and Electrical Engineering Raul Ordonez, Ph.D. Committee Member Professor, Department of Computer and Electrical Engineering John G. Weber, Ph.D. Tony E. Saliba, Ph.D. Associate Dean Dean, School of Engineering School of Engineering & Wilke Distinguished Professor ii c Copyright by Tanner Ryan Adams All rights reserved 2013 ABSTRACT COMPUTATIONALLY EFFICIENT BASIC UNIT RATE CONTROL FOR H.264/AVC Name: Adams, Tanner Ryan University of Dayton Advisor: Dr. Eric J. Balster Video compression has come a long way in the past 15 years. Due to the rise in bandwidth usage, HD video, and other digital media, new and improved methods are required to enable ease of transfer/storage of digital video content. H.264 is the latest and most complex advance video coding standard to date. The complexity is caused from H.264’s vast coding options when it comes to encoding possibilities. While complex, the large number of coding options are what make H.264 perform better than any other standard. Because of these options, compressed video files can vary greatly in the amount of bits used. To solve this dilemma, rate control schemes have been introduced to control data throughput. This thesis presents a method for a computationally efficient rate control algorithm. This algorithm has a low complexity which, in turn, facilitates hardware implementation. iii For my Parents and Grandparents iv ACKNOWLEDGMENTS I would like to thank my friends and family for their support throughout my entire life. I would also like to thank the following people for making my graduate school experience possible: • Thank you Chris McGuinness and Marc Hoffman for helping me to better understand my work and for putting up with my constant questions. • Thank you to the entire ADDA lab for all of your advice during graduate school. • Thank you to Kerry Hill, Al Scarpelli, and the Air Force Research Laboratory for making this experience possible. • Thank you to Dr. Frank Scarpino and Dr. Raul Ordonez for serving on my thesis committee. • Special thanks to Dr. Eric Balster for being one of greatest professors and advisors I have ever had. v TABLE OF CONTENTS ABSTRACT . iii DEDICATION . iv ACKNOWLEDGMENTS . .v LIST OF FIGURES . viii LIST OF TABLES . xi I. Introduction . .1 1.1 Overview of Video Coding . .1 1.2 H.264 Coding Standard . .1 1.2.1 MPEG-2 Visual . .2 1.2.2 H.263 . .2 1.2.3 MPEG-4 Visual . .3 1.3 H.264 Syntax . .3 1.4 H.264 Process . .4 1.5 H.264 Prediction . .5 1.5.1 Intra Prediction . .6 1.5.2 Inter Prediction . .8 1.6 Transform, Quantization and Coding . 10 1.6.1 Transform . 10 1.6.2 DC Transform . 11 1.6.3 Quantization . 12 1.7 Coding . 13 1.7.1 Exp-Golomb Coding . 13 1.7.2 Context Adaptive Variable Length Coding, CAVLC . 15 1.7.3 Context-based Adaptive Binary Arithmetic Coding, CABAC . 15 1.8 Profiles . 16 1.9 Rate Control . 16 1.10 Motive and Organization . 17 vi II. Proposed Rate Control Algorithm . 18 2.1 Introduction . 18 2.2 Baseline MB Level Rate Control . 18 2.3 Proposed BU Rate Control Scheme . 21 2.4 Experimental Results . 26 2.5 Conclusion . 30 III. Intra Prediction . 31 3.1 Overview of Intra Prediction . 31 3.2 Experimental Results . 33 IV. Conclusion and Future Work . 37 4.1 Conclusions . 37 4.2 Future Work . 37 BIBLIOGRAPHY . 39 APPENDICES A. Testing Data for α and β ................................. 41 B. Proposed Rate Control Testing . 49 C. Intra Prediction Mode Data . 56 vii LIST OF FIGURES 1.1 Levels of H.264 . .3 1.2 Motion estimation . .4 1.3 H.264 encoding process . .5 1.4 Macroblock types and sources . .7 1.5 Spatial prediction order . .7 1.6 Intra and inter prediction flow diagram . .8 1.7 Partition sizes of macroblocks . .9 1.8 Predicting from past and future frames . .9 1.9 Forward transform and quantization for Luma and Chroma . 10 1.10 Residual block coding order, 4:2:0 sampling . 12 1.11 Bitstream organization . 14 1.12 Profiles for H.264 . 17 2.1 Design for Baseline MB level rate control . 19 2.2 Flow Char for Baseline MB Level Rate Control . 20 2.3 Design for Baseline BU level rate control . 22 2.4 Design for BU level rate control . 23 viii 2.5 Testing for Foreman at 2 Mbps . 25 2.6 Testing for Stockholm at 15 Mbps . 25 2.7 Arithmetic operations for both systems . 26 2.8 Foreman test sequence at 2 Mbps . 27 2.9 Flower test sequence at 7.5 Mbps . 28 2.10 Stockholm test sequence at 15 Mbps . 29 3.1 Available blocks for intra prediction . 31 3.2 Prediction modes for 8x8 and 4x4 intra prediction . 33 3.3 Encoding time for first three modes against all nine modes for Foreman . 34 3.4 PSNR for first three modes against all nine modes for Foreman . 34 3.5 Encoding time for first three modes against all nine modes for Flower . 35 3.6 PSNR for first three modes against all nine modes for Flower . 36 A.1 Testing for Foreman at 1 Mbps . 42 A.2 Testing for Foreman at 3 Mbps . 43 A.3 Testing for Flower at 5 Mbps . 44 A.4 Testing for Flower at 7.5 Mbps . 45 A.5 Testing for Flower at 10 Mbps . 46 A.6 Testing for Stockholm at 10 Mbps . 47 A.7 Testing for Stockholm at 20 Mbps . 48 B.1 Testing for Foreman at 1 Mbps . 50 B.2 Testing for Foreman at 3 Mbps . 51 ix B.3 Testing for Flower at 5 Mbps . 52 B.4 Testing for Flower at 10 Mbps . 53 B.5 Testing for Stockholm at 10 Mbps . 54 B.6 Testing for Stockholm at 20 Mbps . 55 C.1 Encoding time for first three modes against all nine modes for Foreman . 57 C.2 PSNR for first three modes against all nine modes for Foreman . 58 C.3 Encoding time for first three modes against all nine modes for Flower . 59 C.4 PSNR for first three modes against all nine modes for Flower . 60 x LIST OF TABLES 1.1 Intra Prediction Modes . .6 1.2 Exp-Golomb Coding for code num ......................... 14 2.1 Arithmetic Complexity Calculations . 26 2.2 Rate Distortion Comparison . 28 2.3 Bit Rate Comparison . 29 3.1 Intra Prediction Possibilities . 32 xi.