Entropy Coding of Residual

Total Page:16

File Type:pdf, Size:1020Kb

Entropy Coding of Residual PERFORMANCE AND COMPLEXITY CO-EVALUATIONS OF MPEG4-ALS COMPRESSION STANDARD FOR LOW-LATENCY MUSIC COMPRESSION A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science (Computer Science ) By ISAAC KEVIN MATTHEW M. S. Physics 2 00 8 Wright State University WRIGHT STATE UNIVERSITY SCHOOL OF GRADUATE STUDIES 21 August, 2008 I HEREBY RECOMMEND THAT THE THESIS PREPARED UNDER MY SUPERVISION BY Isaac Kevin Matthew ENTITLED Performance and Complexity Co-evaluation of MPEG4-ALS Compression Standard for Low-latency Music Compression BE ACCEPTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF Master of Science, Computer Science. Dr. Yong Pei (Advisor) Assistant Professor, CS&E Thomas Sudkamp Interim Chair, CS&E Committee on Final Examination Dr. Yong Pei Assistant Professor, CS&E Dr. Bin Wang Associate Professor, CS&E Dr. Thomas Hartrum Assistant Research Professor, CS&E Joseph F. Thomas, Jr., Ph.D. Dean, School of Graduate Studies ABSTRACT Matthew, Isaac Kevin. M.S., Department of Computer Sciences & Engineering, Wright State University, 2008. Performance and Complexity Co-Evaluations of the MPEG4 ALS Compression Standard for Low-Latency Music Compression. In this thesis compression ratio and latency of different classical audio music tracks are analyzed with various encoder options of MPEG4–ALS. Different tracks of audio music tracks are tested with MPEG4-ALS coder with different options to find the optimum values for various parameters to obtain maximum compression ratio with minimum CPU time (encoder and decoder time). Optimum frame length for which the compression ratio saturates for music audio is found out by analyzing the results when different classical music tracks are experimented with various frame lengths. Also music tracks with varying sampling rate are tested and the compression ratio and latency relationship with sampling rate are analyzed and plotted. It is found that the compression gain rate was higher when the codec complexity is less, and joint channel correlation and long term correlations are not significant and latency trade off make the more complex codec options unsuitable for applications where latency is critical. When the two entropy coding options, Rice code and BGMC (Block Gilbert-Moore Codes) are applied on various classical music tracks, it was obvious that the Rice code is more suitable for low-latency applications compared to the more complex BGMC coding, as BGMC improved compression performance with the expense of latency, making it unsuitable in real-time applications. iii TABLE OF CONTENTS LIST OF FIGURES................................................................................................................ VII LIST OF TABLES .................................................................................................................... IX 1. INTRODUCTION ..............................................................................................................1 1.1 Objectives ............................................................................................................................................ 1 1.2 Data Compression .............................................................................................................................. 2 1.3 Speech Coding/Lossy Audio Coding ............................................................................................... 4 1.4 Lossless Audio Coding ....................................................................................................................... 5 1.4.1 The Basic Principle ...................................................................................................................... 6 1.4.2 Filter ............................................................................................................................................... 6 1.4.2.1 Prediction .................................................................................................................... 7 1.4.2.2 Stereo Decorrelation .................................................................................................. 8 1.4.3 Entropy Coding .......................................................................................................................... 9 1.5 Comparison of Lossless Codecs ................................................................................................... 10 1.6 Summary ............................................................................................................................................. 10 1.7 Organization of Thesis ..................................................................................................................... 11 2. INTERACTIVE MULTIMEDIA NETWORK APPLICATION ...................................................... 12 2.1 Telepresence ....................................................................................................................................... 12 2.2 Network Terminology ...................................................................................................................... 14 2.3 Network Delay (Latency) Factors ................................................................................................... 15 2.3.1 Propagation Delay .................................................................................................................... 15 2.3.2 Packetization Delay .................................................................................................................. 16 2.3.3 Processing Delay ...................................................................................................................... 16 2.3.4 Queuing Delay .......................................................................................................................... 17 2.3.5 Transmission Delay .................................................................................................................. 17 2.3.6 Coder Delay .............................................................................................................................. 18 2.3.7 De-Jitter Delay .......................................................................................................................... 18 2.4 Latency Requirment for Real Time Networking .......................................................................... 19 iv 2.5 Music Telepresence ........................................................................................................................... 21 2.5.1 Project Description .................................................................................................................. 22 2.5.2 Features Supported by the Project ........................................................................................ 23 2.5.3 Performance .............................................................................................................................. 24 2.6 Summary ............................................................................................................................................. 26 3. MPEG4-ALS ...................................................................................................................... 27 3.1 MPEG4-ALS Overview ................................................................................................................... 27 3.1.1 General Features ....................................................................................................................... 28 3.1.2 Codec Structure ......................................................................................................................... 29 3.1.2.1 Encoder Structure ........................................................................................................... 29 3.1.2.2 Decoder Structure ........................................................................................................... 31 3.1.3 Linear Predictive Coding .......................................................................................................... 32 3.1.4 Entropy Coding of Residual .................................................................................................... 35 3.1.5 Encoder Options ....................................................................................................................... 36 3.1.5.1 Block Length Switching ........................................................................................... 36 3.1.5.2 Random Access ......................................................................................................... 36 3.1.5.3 Independent Coding ................................................................................................. 37 3.1.5.4 Joint Stereo Coding ................................................................................................... 37 3.1.5.5 Multi-Channel Correlation ....................................................................................... 38 3.2 Tuning MPEG4-ALS for Music Compression ............................................................................ 39 3.2.1 Characteristics of Classical Music .......................................................................................... 40 3.2.2 Codec Complexity .................................................................................................................... 41 3.3 Frame Length ...................................................................................................................................
Recommended publications
  • Lossless Audio Codec Comparison
    Contents Introduction 3 1 CD-audio test 4 1.1 CD's used . .4 1.2 Results all CD's together . .4 1.3 Interesting quirks . .7 1.3.1 Mono encoded as stereo (Dan Browns Angels and Demons) . .7 1.3.2 Compressibility . .9 1.4 Convergence of the results . 10 2 High-resolution audio 13 2.1 Nine Inch Nails' The Slip . 13 2.2 Howard Shore's soundtrack for The Lord of the Rings: The Return of the King . 16 2.3 Wasted bits . 18 3 Multichannel audio 20 3.1 Howard Shore's soundtrack for The Lord of the Rings: The Return of the King . 20 A Motivation for choosing these CDs 23 B Test setup 27 B.1 Scripting and graphing . 27 B.2 Codecs and parameters used . 27 B.3 MD5 checksumming . 28 C Revision history 30 Bibliography 31 2 Introduction While testing the efficiency of lossy codecs can be quite cumbersome (as results differ for each person), comparing lossless codecs is much easier. As the last well documented and comprehensive test available on the internet has been a few years ago, I thought it would be a good idea to update. Beside comparing with CD-audio (which is often done to assess codec performance) and spitting out a grand total, this comparison also looks at extremes that occurred during the test and takes a look at 'high-resolution audio' and multichannel/surround audio. While the comparison was made to update the comparison-page on the FLAC website, it aims to be fair and unbiased.
    [Show full text]
  • An Introduction to Mpeg-4 Audio Lossless Coding
    « ¬ AN INTRODUCTION TO MPEG-4 AUDIO LOSSLESS CODING Tilman Liebchen Technical University of Berlin ABSTRACT encoding process has to be perfectly reversible without loss of in- formation, several parts of both encoder and decoder have to be Lossless coding will become the latest extension of the MPEG-4 implemented in a deterministic way. audio standard. In response to a call for proposals, many com- The MPEG-4 ALS codec uses forward-adaptive Linear Pre- panies have submitted lossless audio codecs for evaluation. The dictive Coding (LPC) to reduce bit rates compared to PCM, leav- codec of the Technical University of Berlin was chosen as refer- ing the optimization entirely to the encoder. Thus, various encoder ence model for MPEG-4 Audio Lossless Coding (ALS), attaining implementations are possible, offering a certain range in terms of working draft status in July 2003. The encoder is based on linear efficiency and complexity. This section gives an overview of the prediction, which enables high compression even with moderate basic encoder and decoder functionality. complexity, while the corresponding decoder is straightforward. The paper describes the basic elements of the codec, points out 2.1. Encoder Overview envisaged applications, and gives an outline of the standardization process. The MPEG-4 ALS encoder (Figure 1) typically consists of these main building blocks: • 1. INTRODUCTION Buffer: Stores one audio frame. A frame is divided into blocks of samples, typically one for each channel. Lossless audio coding enables the compression of digital audio • Coefficients Estimation and Quantization: Estimates (and data without any loss in quality due to a perfect reconstruction quantizes) the optimum predictor coefficients for each of the original signal.
    [Show full text]
  • Cluster-Based Delta Compression of a Collection of Files Department of Computer and Information Science
    Cluster-Based Delta Compression of a Collection of Files Zan Ouyang Nasir Memon Torsten Suel Dimitre Trendafilov Department of Computer and Information Science Technical Report TR-CIS-2002-05 12/27/2002 Cluster-Based Delta Compression of a Collection of Files Zan Ouyang Nasir Memon Torsten Suel Dimitre Trendafilov CIS Department Polytechnic University Brooklyn, NY 11201 Abstract Delta compression techniques are commonly used to succinctly represent an updated ver- sion of a file with respect to an earlier one. In this paper, we study the use of delta compression in a somewhat different scenario, where we wish to compress a large collection of (more or less) related files by performing a sequence of pairwise delta compressions. The problem of finding an optimal delta encoding for a collection of files by taking pairwise deltas can be re- duced to the problem of computing a branching of maximum weight in a weighted directed graph, but this solution is inefficient and thus does not scale to larger file collections. This motivates us to propose a framework for cluster-based delta compression that uses text clus- tering techniques to prune the graph of possible pairwise delta encodings. To demonstrate the efficacy of our approach, we present experimental results on collections of web pages. Our experiments show that cluster-based delta compression of collections provides significant im- provements in compression ratio as compared to individually compressing each file or using tar+gzip, at a moderate cost in efficiency. A shorter version of this paper appears in the Proceedings of the 3rd International Con- ference on Web Information Systems Engineering (WISE), December 2002.
    [Show full text]
  • Implementing Object-Based Audio in Radio Broadcasting
    Object-based Audio in Radio Broadcast Implementing Object-based audio in radio broadcasting Diplomarbeit Ausgeführt zum Zweck der Erlangung des akademischen Grades Dipl.-Ing. für technisch-wissenschaftliche Berufe am Masterstudiengang Digitale Medientechnologien and der Fachhochschule St. Pölten, Masterkalsse Audio Design von: Baran Vlad DM161567 Betreuer/in und Erstbegutachter/in: FH-Prof. Dipl.-Ing Franz Zotlöterer Zweitbegutacher/in:FH Lektor. Dipl.-Ing Stefan Lainer [Wien, 09.09.2019] I Ehrenwörtliche Erklärung Ich versichere, dass - ich diese Arbeit selbständig verfasst, andere als die angegebenen Quellen und Hilfsmittel nicht benutzt und mich auch sonst keiner unerlaubten Hilfe bedient habe. - ich dieses Thema bisher weder im Inland noch im Ausland einem Begutachter/einer Begutachterin zur Beurteilung oder in irgendeiner Form als Prüfungsarbeit vorgelegt habe. Diese Arbeit stimmt mit der vom Begutachter bzw. der Begutachterin beurteilten Arbeit überein. .................................................. ................................................ Ort, Datum Unterschrift II Kurzfassung Die Wissenschaft der objektbasierten Tonherstellung befasst sich mit einer neuen Art der Übermittlung von räumlichen Informationen, die sich von kanalbasierten Systemen wegbewegen, hin zu einem Ansatz, der Ton unabhängig von dem Gerät verarbeitet, auf dem es gerendert wird. Diese objektbasierten Systeme behandeln Tonelemente als Objekte, die mit Metadaten verknüpft sind, welche ihr Verhalten beschreiben. Bisher wurde diese Forschungen vorwiegend
    [Show full text]
  • Ardour Export Redesign
    Ardour Export Redesign Thorsten Wilms [email protected] Revision 2 2007-07-17 Table of Contents 1 Introduction 4 4.5 Endianness 8 2 Insights From a Survey 4 4.6 Channel Count 8 2.1 Export When? 4 4.7 Mapping Channels 8 2.2 Channel Count 4 4.8 CD Marker Files 9 2.3 Requested File Types 5 4.9 Trimming 9 2.4 Sample Formats and Rates in Use 5 4.10 Filename Conflicts 9 2.5 Wish List 5 4.11 Peaks 10 2.5.1 More than one format at once 5 4.12 Blocking JACK 10 2.5.2 Files per Track / Bus 5 4.13 Does it have to be a dialog? 10 2.5.3 Optionally store timestamps 5 5 Track Export 11 2.6 General Problems 6 6 MIDI 12 3 Feature Requests 6 7 Steps After Exporting 12 3.1 Multichannel 6 7.1 Normalize 12 3.2 Individual Files 6 7.2 Trim silence 13 3.3 Realtime Export 6 7.3 Encode 13 3.4 Range ad File Export History 7 7.4 Tag 13 3.5 Running a Script 7 7.5 Upload 13 3.6 Export Markers as Text 7 7.6 Burn CD / DVD 13 4 The Current Dialog 7 7.7 Backup / Archiving 14 4.1 Time Span Selection 7 7.8 Authoring 14 4.2 Ranges 7 8 Container Formats 14 4.3 File vs Directory Selection 8 8.1 libsndfile, currently offered for Export 14 4.4 Container Types 8 8.2 libsndfile, also interesting 14 8.3 libsndfile, rather exotic 15 12 Specification 18 8.4 Interesting 15 12.1 Core 18 8.4.1 BWF – Broadcast Wave Format 15 12.2 Layout 18 8.4.2 Matroska 15 12.3 Presets 18 8.5 Problematic 15 12.4 Speed 18 8.6 Not of further interest 15 12.5 Time span 19 8.7 Check (Todo) 15 12.6 CD Marker Files 19 9 Encodings 16 12.7 Mapping 19 9.1 Libsndfile supported 16 12.8 Processing 19 9.2 Interesting 16 12.9 Container and Encodings 19 9.3 Problematic 16 12.10 Target Folder 20 9.4 Not of further interest 16 12.11 Filenames 20 10 Container / Encoding Combinations 17 12.12 Multiplication 20 11 Elements 17 12.13 Left out 21 11.1 Input 17 13 Credits 21 11.2 Output 17 14 Todo 22 1 Introduction 4 1 Introduction 2 Insights From a Survey The basic purpose of Ardour's export functionality is I conducted a quick survey on the Linux Audio Users to create mixdowns of multitrack arrangements.
    [Show full text]
  • Lossless Audio Codec Comparison
    Contents Introduction 3 1 Test setup 4 1.1 Scripting and graphing . .4 1.2 Codecs and parameters used . .5 1.3 WMA, RealAudio and ALAC . .6 2 CD-audio test 8 2.1 CD's used . .8 2.2 Results all CD's together . .9 2.3 Interesting quirks . 12 2.3.1 Mono encoded as stereo (Dan Browns Angels and Demons) 12 2.4 Convergence of the results . 15 3 High-resolution audio 17 3.1 Nine Inch Nails' The Slip . 17 3.2 Howard Shore's soundtrack for The Lord of the Rings: The Re- turn of the King . 20 3.3 Wasted bits . 22 4 Multichannel audio 24 4.1 Howard Shore's soundtrack for The Lord of the Rings: The Re- turn of the King . 24 A Motivation for choosing these CDs 27 Bibliography 31 2 Introduction While testing the efficiency of lossy codecs can be quite cumbersome (as results differ for each person), comparing lossless codecs is much easier. As the last well documented and comprehensive test available on the internet has been a few years ago, I thought it would be a good idea to update. Beside comparing with CD-audio (which is often done to assess codec perfor- mance) and spitting out a grand total, this comparison also looks at extremes that occurred during the test and takes a look at 'high-resolution audio' and multichannel/surround audio. While the comparison was made to update the comparison-page on the FLAC website, it aims to be fair and unbiased. Because of this, you'll probably won't find anything that looks like conclusions: test results are displayed and analysed, but there is no judgement or choice made.
    [Show full text]
  • Dspic DSC Speex Speech Encoding/Decoding Library As a Development Tool to Emulate and Debug Firmware on a Target Board
    dsPIC® DSC Speex Speech Encoding/Decoding Library User’s Guide © 2008-2011 Microchip Technology Inc. DS70328C Note the following details of the code protection feature on Microchip devices: • Microchip products meet the specification contained in their particular Microchip Data Sheet. • Microchip believes that its family of products is one of the most secure families of its kind on the market today, when used in the intended manner and under normal conditions. • There are dishonest and possibly illegal methods used to breach the code protection feature. All of these methods, to our knowledge, require using the Microchip products in a manner outside the operating specifications contained in Microchip’s Data Sheets. Most likely, the person doing so is engaged in theft of intellectual property. • Microchip is willing to work with the customer who is concerned about the integrity of their code. • Neither Microchip nor any other semiconductor manufacturer can guarantee the security of their code. Code protection does not mean that we are guaranteeing the product as “unbreakable.” Code protection is constantly evolving. We at Microchip are committed to continuously improving the code protection features of our products. Attempts to break Microchip’s code protection feature may be a violation of the Digital Millennium Copyright Act. If such acts allow unauthorized access to your software or other copyrighted work, you may have a right to sue for relief under that Act. Information contained in this publication regarding device Trademarks applications and the like is provided only for your convenience The Microchip name and logo, the Microchip logo, dsPIC, and may be superseded by updates.
    [Show full text]
  • (A/V Codecs) REDCODE RAW (.R3D) ARRIRAW
    What is a Codec? Codec is a portmanteau of either "Compressor-Decompressor" or "Coder-Decoder," which describes a device or program capable of performing transformations on a data stream or signal. Codecs encode a stream or signal for transmission, storage or encryption and decode it for viewing or editing. Codecs are often used in videoconferencing and streaming media solutions. A video codec converts analog video signals from a video camera into digital signals for transmission. It then converts the digital signals back to analog for display. An audio codec converts analog audio signals from a microphone into digital signals for transmission. It then converts the digital signals back to analog for playing. The raw encoded form of audio and video data is often called essence, to distinguish it from the metadata information that together make up the information content of the stream and any "wrapper" data that is then added to aid access to or improve the robustness of the stream. Most codecs are lossy, in order to get a reasonably small file size. There are lossless codecs as well, but for most purposes the almost imperceptible increase in quality is not worth the considerable increase in data size. The main exception is if the data will undergo more processing in the future, in which case the repeated lossy encoding would damage the eventual quality too much. Many multimedia data streams need to contain both audio and video data, and often some form of metadata that permits synchronization of the audio and video. Each of these three streams may be handled by different programs, processes, or hardware; but for the multimedia data stream to be useful in stored or transmitted form, they must be encapsulated together in a container format.
    [Show full text]
  • Lossless Audio Coding Using Adaptive Linear Prediction
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by ScholarBank@NUS LOSSLESS AUDIO CODING USING ADAPTIVE LINEAR PREDICTION SU XIN RONG (B.Eng., SJTU, PRC) A THESIS SUBMITTED FOR THE DEGREE OF MASTER OF ENGINEERING DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING NATIONAL UNIVERSITY OF SINGAPORE 2005 ACKNOWLEDGEMENTS First of all, I would like to take this opportunity to express my deepest gratitude to my supervisor Dr. Huang Dong Yan from Institute for Infocomm Research for her continuous guidance and help, without which this thesis would not have been possible. I would also like to specially thank my supervisor Assistant Professor Nallanathan Arumugam from NUS for his continuous support and help. Finally, I would like to thank all the people who might help me during the project. ii TABLE OF CONTENTS ACKNOWLEDGEMENTS .............................................................................................. ii TABLE OF CONTENTS ................................................................................................. iii SUMMARY ........................................................................................................................vi LIST OF TABLES .......................................................................................................... viii LIST OF FIGURES ...........................................................................................................ix CHAPTER 1 INTRODUCTION.........................................................................................................
    [Show full text]
  • Multimedia Compression Techniques for Streaming
    International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075, Volume-8 Issue-12, October 2019 Multimedia Compression Techniques for Streaming Preethal Rao, Krishna Prakasha K, Vasundhara Acharya most of the audio codes like MP3, AAC etc., are lossy as Abstract: With the growing popularity of streaming content, audio files are originally small in size and thus need not have streaming platforms have emerged that offer content in more compression. In lossless technique, the file size will be resolutions of 4k, 2k, HD etc. Some regions of the world face a reduced to the maximum possibility and thus quality might be terrible network reception. Delivering content and a pleasant compromised more when compared to lossless technique. viewing experience to the users of such locations becomes a The popular codecs like MPEG-2, H.264, H.265 etc., make challenge. audio/video streaming at available network speeds is just not feasible for people at those locations. The only way is to use of this. FLAC, ALAC are some audio codecs which use reduce the data footprint of the concerned audio/video without lossy technique for compression of large audio files. The goal compromising the quality. For this purpose, there exists of this paper is to identify existing techniques in audio-video algorithms and techniques that attempt to realize the same. compression for transmission and carry out a comparative Fortunately, the field of compression is an active one when it analysis of the techniques based on certain parameters. The comes to content delivering. With a lot of algorithms in the play, side outcome would be a program that would stream the which one actually delivers content while putting less strain on the audio/video file of our choice while the main outcome is users' network bandwidth? This paper carries out an extensive finding out the compression technique that performs the best analysis of present popular algorithms to come to the conclusion of the best algorithm for streaming data.
    [Show full text]
  • Preview - Click Here to Buy the Full Publication
    This is a preview - click here to buy the full publication IEC 62481-2 ® Edition 2.0 2013-09 INTERNATIONAL STANDARD colour inside Digital living network alliance (DLNA) home networked device interoperability guidelines – Part 2: DLNA media formats INTERNATIONAL ELECTROTECHNICAL COMMISSION PRICE CODE XH ICS 35.100.05; 35.110; 33.160 ISBN 978-2-8322-0937-0 Warning! Make sure that you obtained this publication from an authorized distributor. ® Registered trademark of the International Electrotechnical Commission This is a preview - click here to buy the full publication – 2 – 62481-2 © IEC:2013(E) CONTENTS FOREWORD ......................................................................................................................... 20 INTRODUCTION ................................................................................................................... 22 1 Scope ............................................................................................................................. 23 2 Normative references ..................................................................................................... 23 3 Terms, definitions and abbreviated terms ....................................................................... 30 3.1 Terms and definitions ............................................................................................ 30 3.2 Abbreviated terms ................................................................................................. 34 3.4 Conventions .........................................................................................................
    [Show full text]
  • Name Synopsis Description
    SHNTOOL(1) local SHNTOOL(1) NAME shntool − a multi-purpose WAV Edata processing and reporting utility SYNOPSIS shntool mode ... shntool [CORE OPTION] DESCRIPTION shntool is a command-line utility to viewand/or modify WAV Edata and properties. It runs in several dif- ferent operating modes, and supports various lossless audio formats. shntool is comprised of three parts - its core, mode modules, and format modules. This helps to makethe code easier to maintain, as well as aid other programmers in developing newfunctionality.The distribution archive contains a file named ’modules.howto’ that describes howtocreate a newmode or format module, for those so inclined. Mode modules shntool performs various functions on WAV Edata through the use of mode modules. The core of shntool is simply a wrapper around the mode modules. In fact, when shntool is run with a valid mode as its first argument, it essentially runs the main procedure for the specified mode, and quits. shntool comes with sev- eral built-in modes, described below: len Displays length, size and properties of PCM WAV Edata fix Fixes sector-boundary problems with CD-quality PCM WAV Edata hash Computes the MD5 or SHA1 fingerprint of PCM WAV Edata pad Pads CD(hyquality files not aligned on sector boundaries with silence join Joins PCM WAV Edata from multiple files into one split Splits PCM WAV Edata from one file into multiple files cat Writes PCM WAV Edata from one or more files to the terminal cmp Compares PCM WAV Edata in twofiles cue Generates a CUE sheet or split points from a set of files conv Converts files from one format to another info Displays detailed information about PCM WAV Edata strip Strips extra RIFF chunks and/or writes canonical headers gen Generates CD-quality PCM WAV Edata files containing silence trim Trims PCM WAV Esilence from the ends of files Formore information on the meaning of the various command-line options for each mode, see the MODE- SPECIFIC OPTIONS section below.
    [Show full text]