Eb-2013-00233 INCITS International Committee for Information

Total Page:16

File Type:pdf, Size:1020Kb

Eb-2013-00233 INCITS International Committee for Information eb-2013-00233 INCITS International Committee for Information Technology Standards INCITS Secretariat, Information Technology Industry Council (ITI) 1101 K Street, NW, Suite 610, Washington, DC 20005 Date: February 6, 2013 Ref. Doc.: eb-2012-01071 Reply to: Deborah J. Spittle, Associate Manager, Standards Operations Phone: 202-626-5746 Email: [email protected] Notification of Public Review and Comments Register for the Reaffirmations of National Standards in INCITS/L3. The public review period is from February 15, 2013 April 1, 2013. INCITS/ISO/IEC 9281-2:1990[R2008] Information technology - Picture Coding Methods - Part 2: Procedure for Registration INCITS/ISO/IEC 9281-1:1990[R2008] Information technology - Picture Coding Methods - Part 1: Identification INCITS/ISO/IEC 9282-1:1988[R2008] Information technology - Coded Representation of Computer Graphics Images - Part 1: Encoding principles for picture representation in a 7-bit or 8-bit environment INCITS/ISO/IEC 14496-5:2001/AM Information technology - Coding of audio-visual objects - Part 5: 2:2003[R2008] Reference software AMENDMENT 2: MPEG-4 Reference software extensions for XMT and media modes INCITS/ISO/IEC 21000-2:2005[2008] Information technology - Multimedia Framework (MPEG-21) - Part 2: Digital Item Declaration INCITS/ISO/IEC 14496- Information technology - Coding of audio-visual objects - Part 5: 5:2001/AM1:2002[R2008] Reference software - Amendment 1: Reference software for MPEG-4 INCITS/ISO/IEC 13818-2:2000/AM Information technology - Generic coding of moving pictures and 1:2001[R2008] associated audio information - Part 2: Video AMENDMENT 1: Content description data INCITS/ISO/IEC 11172-1:1993[R2008] Information technology - Coding of moving pictures and associated audio for digital storage media at up to about 1,5 Mbit/s - Part 1: System Integration INCITS/ISO/IEC 11172-2:1993[R2008] Information technology - Coding of moving pictures and associated audio for digital storage media at up to about 1,5 Mbit/s - Part 2: Video Compression INCITS/ISO/IEC 14496-5:2001[R2008] Information technology - Coding of audio-visual objects - Part 5: Reference software (Second edition) INCITS/ISO/IEC 21000-3:2003[R2008] Information technology - Multimedia Framework (MPEG-21) - Part 3: Digital Item Identification and Description INCITS/ISO/IEC 15938-5:2003[R2008] Information technology - Multimedia content description interface - Part 5: Multimedia description schemes INCITS/ISO/IEC 15938-6:2003[R2008] Information technology - Multimedia content description interface - Part 6: Reference software INCITS/ISO/IEC 15938-7:2003[R2008] Information technology - MPEG-7- Coding of auditory-visual objects: Information technology - Multimedia content description interface - Part 7: Conformance testing INCITS/ISO/IEC 11172-3:1993[R2008] Information technology - Coding of moving pictures and associated audio for digital storage media at up to about 1,5 Mbit/s - Part 3: Audio Compression INCITS/ISO/IEC 11172-4:1995[R2008] Information technology - Coding of moving pictures and associated audio for digital storage media at up to about 1,5 Mbit/s - Part 4: Compliance Testing INCITS/ISO/IEC 14496-14:2003[R2008] Information technology - Coding of audio-visual objects - Part 14: MP4 file format INCITS/ISO/IEC 15444-6:2003[R2008] Information technology - JPEG 2000 Image Coding System - Part 6: Compound image file format INCITS/ISO/IEC 10918-3:1997[R2008] Information technology - Digital Compression and coding of continuous- tone still images - Part 3: Extensions INCITS/ISO/IEC 15444-2:2004[2008] Information technology - JPEG 2000 Image Coding System - Part 2: Extensions INCITS/ISO/IEC 15444-3:2007[2008] Information technology -- JPEG 2000 image coding system: Motion JPEG 2000, Part 3 INCITS/ISO/IEC 14495-2:2003[R2008] Information technology - Lossless and near-lossless compression of continuous-tone still images - Part 2: Extension INCITS/ISO/IEC 10918-2:1995[R2008] Information technology - Digital Compression and coding of continuous- tone still images - Part 2: Compliance Testing INCITS/ISO/IEC 15444- Information technology - JPEG 2000 Image Coding System - Part 2: 2:2004/AM2:2006[2008] Extensions AMENDMENT 2: Extended capabilities marker segment INCITS/ISO/IEC 11544:1993[R2008] Information technology - Coded Representation of picture and audio Information - Progressive bi-level Image Compression (JBIG) INCITS/ISO/IEC 10918-1:1994[R2008] Information technology - Digital Compression and coding of continuous- tone still images - Part 1: Requirements and guidelines INCITS/ISO/IEC 15444-4:2004[2008] Information technology - JPEG 2000 Image Coding System - Part 4: Conformance testing If the action is to accept in whole or in part a proposal contained in the comment, the changes should be sent to the Associate Manager of Standards Operations together with any comments supporting the change. If the action is to reject in whole or in part proposals contained in the comment, the response should provide the rationale for the rejection. The comment should be discussed at the next meeting, and if not definitively responded to at once, an interim acknowledgment should be sent along with an estimated date of action. The final response to the commenter must include the provision that the commenter has twenty working days from the postmark of the committee’s response to indicate, in a written statement, acceptance or rejection of the response. No comments have been received to date. .
Recommended publications
  • Free Lossless Image Format
    FREE LOSSLESS IMAGE FORMAT Jon Sneyers and Pieter Wuille [email protected] [email protected] Cloudinary Blockstream ICIP 2016, September 26th DON’T WE HAVE ENOUGH IMAGE FORMATS ALREADY? • JPEG, PNG, GIF, WebP, JPEG 2000, JPEG XR, JPEG-LS, JBIG(2), APNG, MNG, BPG, TIFF, BMP, TGA, PCX, PBM/PGM/PPM, PAM, … • Obligatory XKCD comic: YES, BUT… • There are many kinds of images: photographs, medical images, diagrams, plots, maps, line art, paintings, comics, logos, game graphics, textures, rendered scenes, scanned documents, screenshots, … EVERYTHING SUCKS AT SOMETHING • None of the existing formats works well on all kinds of images. • JPEG / JP2 / JXR is great for photographs, but… • PNG / GIF is great for line art, but… • WebP: basically two totally different formats • Lossy WebP: somewhat better than (moz)JPEG • Lossless WebP: somewhat better than PNG • They are both .webp, but you still have to pick the format GOAL: ONE FORMAT THAT COMPRESSES ALL IMAGES WELL EXPERIMENTAL RESULTS Corpus Lossless formats JPEG* (bit depth) FLIF FLIF* WebP BPG PNG PNG* JP2* JXR JLS 100% 90% interlaced PNGs, we used OptiPNG [21]. For BPG we used [4] 8 1.002 1.000 1.234 1.318 1.480 2.108 1.253 1.676 1.242 1.054 0.302 the options -m 9 -e jctvc; for WebP we used -m 6 -q [4] 16 1.017 1.000 / / 1.414 1.502 1.012 2.011 1.111 / / 100. For the other formats we used default lossless options. [5] 8 1.032 1.000 1.099 1.163 1.429 1.664 1.097 1.248 1.500 1.017 0.302� [6] 8 1.003 1.000 1.040 1.081 1.282 1.441 1.074 1.168 1.225 0.980 0.263 Figure 4 shows the results; see [22] for more details.
    [Show full text]
  • Quadtree Based JBIG Compression
    Quadtree Based JBIG Compression B. Fowler R. Arps A. El Gamal D. Yang ISL, Stanford University, Stanford, CA 94305-4055 ffowler,arps,abbas,[email protected] Abstract A JBIG compliant, quadtree based, lossless image compression algorithm is describ ed. In terms of the numb er of arithmetic co ding op erations required to co de an image, this algorithm is signi cantly faster than previous JBIG algorithm variations. Based on this criterion, our algorithm achieves an average sp eed increase of more than 9 times with only a 5 decrease in compression when tested on the eight CCITT bi-level test images and compared against the basic non-progressive JBIG algorithm. The fastest JBIG variation that we know of, using \PRES" resolution reduction and progressive buildup, achieved an average sp eed increase of less than 6 times with a 7 decrease in compression, under the same conditions. 1 Intro duction In facsimile applications it is desirable to integrate a bilevel image sensor with loss- less compression on the same chip. Suchintegration would lower p ower consumption, improve reliability, and reduce system cost. To reap these b ene ts, however, the se- lection of the compression algorithm must takeinto consideration the implementation tradeo s intro duced byintegration. On the one hand, integration enhances the p os- sibility of parallelism which, if prop erly exploited, can sp eed up compression. On the other hand, the compression circuitry cannot b e to o complex b ecause of limitations on the available chip area. Moreover, most of the chip area on a bilevel image sensor must b e o ccupied by photo detectors, leaving only the edges for digital logic.
    [Show full text]
  • MPEG Compression Is Based on Processing 8 X 8 Pixel Blocks
    MPEG-1 & MPEG-2 Compression 6th of March, 2002, Mauri Kangas Contents: • MPEG Background • MPEG-1 Standard (shortly) • MPEG-2 Standard (shortly) • MPEG-1 and MPEG-2 Differencies • MPEG Encoding and Decoding • Colour sub-sampling • Motion Compensation • Slices, macroblocks, blocks, etc. • DCT • MPEG-2 bit stream syntax • MPEG-2 • Supported Features • Levels • Profiles • DVB Systems 1 © Mauri Kangas 2002 MPEG-1,2.PPT/ 24.02.2002 / Mauri Kangas MPEG Background • MPEG = Motion Picture Expert Group • ISO/IEC JTC1/SC29 • WG11 Motion Picture Experts Group (MPEG) • WG10 Joint Photographic Experts Group (JPEG) • WG7 Computer Graphics Experts Group (CGEG) • WG9 Joint Bi-level Image coding experts Group (JBIG) • WG12 Multimedia and Hypermedia information coding Experts Group (MHEG) • MPEG-1,2 Standardization 1988- • Requirement • System • Video • Audio • Implementation • Testing • Latest MPEG Standardization: MPEG-4, MPEG-7, MPEG-21 2 © Mauri Kangas 2002 MPEG-1,2.PPT/ 24.02.2002 / Mauri Kangas MPEG-1 Standard ISO/IEC 11172-2 (1991) "Coding of moving pictures and associated audio for digital storage media" Video • optimized for bitrates around 1.5 Mbit/s • originally optimized for SIF picture format, but not limited to it: • 352x240 pixels a 30 frames/sec [ NTSC based ] • 352x288 pixels at 25 frames/sec [ PAL based ] • progressive frames only - no direct provision for interlaced video applications, such as broadcast television Audio • joint stereo audio coding at 192 kbit/s (layer 2) System • mainly designed for error-free digital storage media •
    [Show full text]
  • CISC 3635 [36] Multimedia Coding and Compression
    Brooklyn College Department of Computer and Information Sciences CISC 3635 [36] Multimedia Coding and Compression 3 hours lecture; 3 credits Media types and their representation. Multimedia coding and compression. Lossless data compression. Lossy data compression. Compression standards: text, audio, image, fax, and video. Course Outline: 1. Media Types and Their Representations (Week 1-2) a. Text b. Analog and Digital Audio c. Digitization of Sound d. Musical Instrument Digital Interface (MIDI) e. Audio Coding: Pulse Code Modulation (PCM) f. Graphics and Images Data Representation g. Image File Formats: GIF, JPEG, PNG, TIFF, BMP, etc. h. Color Science and Models i. Fax j. Video Concepts k. Video Signals: Component, Composite, S-Video l. Analog and Digital Video: NTSC, PAL, SECAM, HDTV 2. Lossless Compression Algorithms (Week 3-4) a. Basics of Information Theory b. Run-Length Coding c. Variable Length Coding: Huffman Coding d. Basic Fax Compression e. Dictionary Based Coding: LZW Compression f. Arithmetic Coding g. Lossless Image Compression 3. Lossy Compression Algorithms (Week 5-6) a. Distortion Measures b. Quantization c. Transform Coding d. Wavelet Based Coding e. Embedded Zerotree of Wavelet (EZW) Coefficients 4. Basic Audio Compression (Week 7-8) a. Differential Coders: DPCM, ADPCM, DM b. Vocoders c. Linear Predictive Coding (LPC) d. CELP e. Audio Standards: G.711, G.726, G.723, G.728. G.729, etc. 5. Image Compression Standards (Week 9) a. The JPEG Standard b. JPEG 2000 c. JPEG-LS d. Bilevel Image Compression Standards: JBIG, JBIG2 6. Basic Video Compression (Week 10) a. Video Compression Based on Motion Compensation b. Search for Motion Vectors c.
    [Show full text]
  • Analysis and Comparison of Compression Algorithm for Light Field Mask
    International Journal of Applied Engineering Research ISSN 0973-4562 Volume 12, Number 12 (2017) pp. 3553-3556 © Research India Publications. http://www.ripublication.com Analysis and Comparison of Compression Algorithm for Light Field Mask Hyunji Cho1 and Hoon Yoo2* 1Department of Computer Science, SangMyung University, Korea. 2Associate Professor, Department of Media Software SangMyung University, Korea. *Corresponding author Abstract This paper describes comparison and analysis of state-of-the- art lossless image compression algorithms for light field mask data that are very useful in transmitting and refocusing the light field images. Recently, light field cameras have received wide attention in that they provide 3D information. Also, there has been a wide interest in studying the light field data compression due to a huge light field data. However, most of existing light field compression methods ignore the mask information which is one of important features of light field images. In this paper, we reports compression algorithms and further use this to achieve binary image compression by realizing analysis and comparison of the standard compression methods such as JBIG, JBIG 2 and PNG algorithm. The results seem to confirm that the PNG method for text data compression provides better results than the state-of-the-art methods of JBIG and JBIG2 for binary image compression. Keywords: Lossless compression, Image compression, Light Figure. 2. Basic architecture from raw images to RGB and filed compression, Plenoptic coding mask images INTRODUCTION The LF camera provides a raw image captured from photosensor with microlens, as depicted in Fig. 1. The raw Light field (LF) cameras, also referred to as plenoptic cameras, data consists of 10 bits per pixel precision in little-endian differ from regular cameras by providing 3D information of format.
    [Show full text]
  • Lossless Image Compression
    Lossless Image Compression C.M. Liu Perceptual Signal Processing Lab College of Computer Science National Chiao-Tung University http://www.csie.nctu.edu.tw/~cmliu/Courses/Compression/ Office: EC538 (03)5731877 [email protected] Lossless JPEG (1992) 2 ITU Recommendation T.81 (09/92) Compression based on 8 predictive modes ( “selection values): 0 P(x) = x (no prediction) 1 P(x) = W 2 P(x) = N 3 P(x) = NW NW N 4 P(x) = W + N - NW 5 P(x) = W + ⎣(N-NW)/2⎦ W x 6 P(x) = N + ⎣(W-NW)/2⎦ 7 P(x) = ⎣(W + N)/2⎦ Sequence is then entropy-coded (Huffman/AC) Lossless JPEG (2) 3 Value 0 used for differential coding only in hierarchical mode Values 1, 2, 3 One-dimensional predictors Values 4, 5, 6, 7 Two-dimensional Value 1 (W) Used in the first line of samples At the beginning of each restart Selected predictor used for the other lines Value 2 (N) Used at the start of each line, except first P-1 Default predictor value: 2 At the start of first line Beginning of each restart Lossless JPEG Performance 4 JPEG prediction mode comparisons JPEG vs. GIF vs. PNG Context-Adaptive Lossless Image Compression [Wu 95/96] 5 Two modes: gray-scale & bi-level We are skipping the lossy scheme for now Basic ideas find the best context from the info available to encoder/decoder estimate the presence/lack of horizontal/vertical features CALIC: Initial Prediction 6 if dh−dv > 80 // sharp horizontal edge X* = N else if dv−dh > 80 // sharp vertical edge X* = W else { // assume smoothness first X* = (N+W)/2 +(NE−NW)/4 if dh−dv > 32 // horizontal edge X* = (X*+N)/2
    [Show full text]
  • JBIG-Like Coding of Bi-Level Image Data in JPEG-2000
    ISO/IEC JTC 1/SC 29/WG1 N1014 Date: 1998-10- 20 ISO/IEC JTC 1/SC 29/WG 1 (ITU-T SG8) Coding of Still Pictures JBIG JPEG Joint Bi-level Image Joint Photographic Experts Group Experts Group TITLE: Report on Core Experiment CodEff26: JBIG-Like Coding of Bi-Level Image Data in JPEG-2000 SOURCE: Faouzi Kossentini ([email protected]) and Dave Tompkins Department of ECE, University of BC, Vancouver, BC, Canada V6T 1Z4 Soeren Forchhammer ([email protected]), Bo Martins and Ole Jensen Department of Telecommunication, TDU, Lyngby, Denmark, DK-2800 Ian Caven, Image Power Inc., Vancouver, BC, Canada V6E 4B1 Paul Howard, AT&T Labs, NJ, USA PROJECT: JPEG-2000 STATUS: Core Experiment Results REQUESTED ACTION: Discussion DISTRIBUTION: 14th Meeting of ISO/IEC JTC1/SC 29/WG1 Contact: ISO/IEC JTC 1/SC 29/WG 1 Convener - Dr. Daniel T. Lee Hewlett-Packard Company, 11000 Wolfe Road, MS42U0, Cupertion, California 95014, USA Tel: +1 408 447 4160, Fax: +1 408 447 2842, E-mail: [email protected] 2 1. Update This document updates results previously reported in WG1N863. Specifically, the upcoming JBIG-2 Verification Model (VM) was used to generate the compression rates in Table 1. These results more accurately reflect the expected bit rates, and include the overhead required for the proper JBIG-2 bitstream formatting. Results may be better in the final implementation, but these results are guaranteed to be attainable with the current VM. The JBIG-2 VM will be available in December 1998. 2. Summary This document presents experimental results that compare the compression performance several JBIG-like coders to the VM0 baseline coder.
    [Show full text]
  • Coding and Compression
    Chapter 3 Multimedia Systems Technology: Co ding and Compression 3.1 Intro duction In multimedia system design, storage and transport of information play a sig- ni cant role. Multimedia information is inherently voluminous and therefore requires very high storage capacity and very high bandwidth transmission capacity.For instance, the storage for a video frame with 640 480 pixel resolution is 7.3728 million bits, if we assume that 24 bits are used to en- co de the luminance and chrominance comp onents of each pixel. Assuming a frame rate of 30 frames p er second, the entire 7.3728 million bits should b e transferred in 33.3 milliseconds, which is equivalent to a bandwidth of 221.184 million bits p er second. That is, the transp ort of such large number of bits of information and in such a short time requires high bandwidth. Thereare two approaches that arepossible - one to develop technologies to provide higher bandwidth of the order of Gigabits per second or more and the other to nd ways and means by which the number of bits to betransferred can be reduced, without compromising the information content. It amounts to saying that we need a transformation of a string of characters in some representation such as ASCI I into a new string e.g., of bits that contains the same information but whose length must b e as small as p ossible; i.e., data compression. Data compression is often referred to as co ding, whereas co ding is a general term encompassing any sp ecial representation of data that achieves a given goal.
    [Show full text]
  • Forcepoint DLP Supported File Formats and Size Limits
    Forcepoint DLP Supported File Formats and Size Limits Supported File Formats and Size Limits | Forcepoint DLP | v8.8.1 This article provides a list of the file formats that can be analyzed by Forcepoint DLP, file formats from which content and meta data can be extracted, and the file size limits for network, endpoint, and discovery functions. See: ● Supported File Formats ● File Size Limits © 2021 Forcepoint LLC Supported File Formats Supported File Formats and Size Limits | Forcepoint DLP | v8.8.1 The following tables lists the file formats supported by Forcepoint DLP. File formats are in alphabetical order by format group. ● Archive For mats, page 3 ● Backup Formats, page 7 ● Business Intelligence (BI) and Analysis Formats, page 8 ● Computer-Aided Design Formats, page 9 ● Cryptography Formats, page 12 ● Database Formats, page 14 ● Desktop publishing formats, page 16 ● eBook/Audio book formats, page 17 ● Executable formats, page 18 ● Font formats, page 20 ● Graphics formats - general, page 21 ● Graphics formats - vector graphics, page 26 ● Library formats, page 29 ● Log formats, page 30 ● Mail formats, page 31 ● Multimedia formats, page 32 ● Object formats, page 37 ● Presentation formats, page 38 ● Project management formats, page 40 ● Spreadsheet formats, page 41 ● Text and markup formats, page 43 ● Word processing formats, page 45 ● Miscellaneous formats, page 53 Supported file formats are added and updated frequently. Key to support tables Symbol Description Y The format is supported N The format is not supported P Partial metadata
    [Show full text]
  • Introduction to the Special Issue on Scalable Video Coding—Standardization and Beyond
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, VOL. 17, NO. 9, SEPTEMBER 2007 1099 Introduction to the Special Issue on Scalable Video Coding—Standardization and Beyond FEW YEARS ago, the subject of video coding received of scalability, this one is perhaps the most difficult to design Aa large amount of skepticism. The basic argument was in a way that is both effective (from a compression capability that the 1990s generation of international standards was close point of view) and practical for implementation in terms of to the asymptotic limit of compression capability—or at least computational resource requirements. Finally, there is quality was good enough that there would be little market interest in scalability, sometimes also referred to as SNR or fidelity scala- something else. Moreover, there was the fear that a new video bility, in which the enhancement layer provides an increase in codec design created by an open committee process would in- video quality without changing the picture resolution. evitably contain so many compromises and take so long to be For example, 1080p50/60 enhancement of today’s 720p50/60 completed that it would fail to meet real industry needs or to be or 1080i25/30 HDTV can be deployed as a premium service state-of-the-art in capability when finished. while retaining full compatibility with deployed receivers, or The Joint Video Team (JVT) then proved those views HDTV can be deployed as an enhancement of SDTV video to be wrong and revitalized the field of video coding with services. Another example is low-delay adaptation for multi- the 2003 creation of the H.264/AVC standard (ITU-T Rec.
    [Show full text]
  • On the Applications of Multimedia Processing to Communications
    Scanning the Technology On the Applications of Multimedia Processing to Communications RICHARD V. COX, FELLOW, IEEE, BARRY G. HASKELL, FELLOW, IEEE, YANN LECUN, MEMBER, IEEE, BEHZAD SHAHRARAY, MEMBER, IEEE, AND LAWRENCE RABINER, FELLOW, IEEE Invited Paper The challenge of multimedia processing is to provide services Keywords—AAC, access, agents, audio coding, cable modems, that seamlessly integrate text, sound, image, and video informa- communications networks, content-based video sampling, docu- tion and to do it in a way that preserves the ease of use and ment compression, fax coding, H.261, HDTV, image coding, image interactivity of conventional plain old telephone service (POTS) processing, JBIG, JPEG, media conversion, MPEG, multimedia, telephony, irrelevant of the bandwidth or means of access of the multimedia browsing, multimedia indexing, multimedia searching, optical character recognition, PAC, packet networks, perceptual connection to the service. To achieve this goal, there are a number coding, POTS telephony, quality of service, speech coding, speech of technological problems that must be considered, including: compression, speech processing, speech recognition, speech syn- • compression and coding of multimedia signals, including thesis, spoken language interface, spoken language understanding, algorithmic issues, standards issues, and transmission issues; standards, streaming, teleconferencing, video coding, video tele- phony. • synthesis and recognition of multimedia signals, including speech, images, handwriting, and text; • organization, storage, and retrieval of multimedia signals, I. INTRODUCTION including the appropriate method and speed of delivery (e.g., streaming versus full downloading), resolution (including In a very real sense, virtually every individual has had layering or embedded versions of the signal), and quality of experience with multimedia systems of one type or another.
    [Show full text]
  • Iso/Iec Standard 12087-3
    This is a preview - click here to buy the full publication INTERNATIONAL ISO/IEC STANDARD 12087-3 First edition 1995-02-15 Information technology - Computer graphics and image processing - Image Processing and Interchange (IPI) - Functional specification - Part 3: Image Interchange Facility (HF) Technologies de I’information - Infographie et traitement de I’image - Traitement de I’image et behange (/PI) - Spkcifica tion fonctionnelle - Partie 3: Accessoires pour I’khange d’images (HF) J Reference number ISO/1 EC 12087-3: 1995(E) This is a preview - click here to buy the full publication ISO/IEC 12087-3: 1995(E) Contents Foreword ................................................................................................................................................... iv Introduction ............................................................................................................................................... V Scope ................................................................................................................................................... .. 1 Normative references ........................................................................................................................... 3 Definitions and abbreviations ............................................................................................................... 5 3.1 Defini tions ................................................................................................................................. 5 3.2 Abbreviations
    [Show full text]