Introduction to the Special Issue on Scalable Video Coding—Standardization and Beyond
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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. -
Versatile Video Coding – the Next-Generation Video Standard of the Joint Video Experts Team
31.07.2018 Versatile Video Coding – The Next-Generation Video Standard of the Joint Video Experts Team Mile High Video Workshop, Denver July 31, 2018 Gary J. Sullivan, JVET co-chair Acknowledgement: Presentation prepared with Jens-Rainer Ohm and Mathias Wien, Institute of Communication Engineering, RWTH Aachen University 1. Introduction Versatile Video Coding – The Next-Generation Video Standard of the Joint Video Experts Team 1 31.07.2018 Video coding standardization organisations • ISO/IEC MPEG = “Moving Picture Experts Group” (ISO/IEC JTC 1/SC 29/WG 11 = International Standardization Organization and International Electrotechnical Commission, Joint Technical Committee 1, Subcommittee 29, Working Group 11) • ITU-T VCEG = “Video Coding Experts Group” (ITU-T SG16/Q6 = International Telecommunications Union – Telecommunications Standardization Sector (ITU-T, a United Nations Organization, formerly CCITT), Study Group 16, Working Party 3, Question 6) • JVT = “Joint Video Team” collaborative team of MPEG & VCEG, responsible for developing AVC (discontinued in 2009) • JCT-VC = “Joint Collaborative Team on Video Coding” team of MPEG & VCEG , responsible for developing HEVC (established January 2010) • JVET = “Joint Video Experts Team” responsible for developing VVC (established Oct. 2015) – previously called “Joint Video Exploration Team” 3 Versatile Video Coding – The Next-Generation Video Standard of the Joint Video Experts Team Gary Sullivan | Jens-Rainer Ohm | Mathias Wien | July 31, 2018 History of international video coding standardization -
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. -
Security Solutions Y in MPEG Family of MPEG Family of Standards
1 Security solutions in MPEG family of standards TdjEbhiiTouradj Ebrahimi [email protected] NET working? Broadcast Networks and their security 16-17 June 2004, Geneva, Switzerland MPEG: Moving Picture Experts Group 2 • MPEG-1 (1992): MP3, Video CD, first generation set-top box, … • MPEG-2 (1994): Digital TV, HDTV, DVD, DVB, Professional, … • MPEG-4 (1998, 99, ongoing): Coding of Audiovisual Objects • MPEG-7 (2001, ongo ing ): DitiDescription of Multimedia Content • MPEG-21 (2002, ongoing): Multimedia Framework NET working? Broadcast Networks and their security 16-17 June 2004, Geneva, Switzerland MPEG-1 - ISO/IEC 11172:1992 3 • Coding of moving pictures and associated audio for digital storage media at up to about 1,5 Mbit/s – Part 1 Systems - Program Stream – Part 2 Video – Part 3 Audio – Part 4 Conformance – Part 5 Reference software NET working? Broadcast Networks and their security 16-17 June 2004, Geneva, Switzerland MPEG-2 - ISO/IEC 13818:1994 4 • Generic coding of moving pictures and associated audio – Part 1 Systems - joint with ITU – Part 2 Video - joint with ITU – Part 3 Audio – Part 4 Conformance – Part 5 Reference software – Part 6 DSM CC – Par t 7 AAC - Advance d Au dio Co ding – Part 9 RTI - Real Time Interface – Part 10 Conformance extension - DSM-CC – Part 11 IPMP on MPEG-2 Systems NET working? Broadcast Networks and their security 16-17 June 2004, Geneva, Switzerland MPEG-4 - ISO/IEC 14496:1998 5 • Coding of audio-visual objects – Part 1 Systems – Part 2 Visual – Part 3 Audio – Part 4 Conformance – Part 5 Reference -
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 • -
The H.264 Advanced Video Coding (AVC) Standard
Whitepaper: The H.264 Advanced Video Coding (AVC) Standard What It Means to Web Camera Performance Introduction A new generation of webcams is hitting the market that makes video conferencing a more lifelike experience for users, thanks to adoption of the breakthrough H.264 standard. This white paper explains some of the key benefits of H.264 encoding and why cameras with this technology should be on the shopping list of every business. The Need for Compression Today, Internet connection rates average in the range of a few megabits per second. While VGA video requires 147 megabits per second (Mbps) of data, full high definition (HD) 1080p video requires almost one gigabit per second of data, as illustrated in Table 1. Table 1. Display Resolution Format Comparison Format Horizontal Pixels Vertical Lines Pixels Megabits per second (Mbps) QVGA 320 240 76,800 37 VGA 640 480 307,200 147 720p 1280 720 921,600 442 1080p 1920 1080 2,073,600 995 Video Compression Techniques Digital video streams, especially at high definition (HD) resolution, represent huge amounts of data. In order to achieve real-time HD resolution over typical Internet connection bandwidths, video compression is required. The amount of compression required to transmit 1080p video over a three megabits per second link is 332:1! Video compression techniques use mathematical algorithms to reduce the amount of data needed to transmit or store video. Lossless Compression Lossless compression changes how data is stored without resulting in any loss of information. Zip files are losslessly compressed so that when they are unzipped, the original files are recovered. -
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. -
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. -
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 -
ITC Confplanner DVD Pages Itcconfplanner
Comparative Analysis of H.264 and Motion- JPEG2000 Compression for Video Telemetry Item Type text; Proceedings Authors Hallamasek, Kurt; Hallamasek, Karen; Schwagler, Brad; Oxley, Les Publisher International Foundation for Telemetering Journal International Telemetering Conference Proceedings Rights Copyright © held by the author; distribution rights International Foundation for Telemetering Download date 25/09/2021 09:57:28 Link to Item http://hdl.handle.net/10150/581732 COMPARATIVE ANALYSIS OF H.264 AND MOTION-JPEG2000 COMPRESSION FOR VIDEO TELEMETRY Kurt Hallamasek, Karen Hallamasek, Brad Schwagler, Les Oxley [email protected] Ampex Data Systems Corporation Redwood City, CA USA ABSTRACT The H.264/AVC standard, popular in commercial video recording and distribution, has also been widely adopted for high-definition video compression in Intelligence, Surveillance and Reconnaissance and for Flight Test applications. H.264/AVC is the most modern and bandwidth-efficient compression algorithm specified for video recording in the Digital Recording IRIG Standard 106-11, Chapter 10. This bandwidth efficiency is largely derived from the inter-frame compression component of the standard. Motion JPEG-2000 compression is often considered for cockpit display recording, due to the concern that details in the symbols and graphics suffer excessively from artifacts of inter-frame compression and that critical information might be lost. In this paper, we report on a quantitative comparison of H.264/AVC and Motion JPEG-2000 encoding for HD video telemetry. Actual encoder implementations in video recorder products are used for the comparison. INTRODUCTION The phenomenal advances in video compression over the last two decades have made it possible to compress the bit rate of a video stream of imagery acquired at 24-bits per pixel (8-bits for each of the red, green and blue components) with a rate of a fraction of a bit per pixel. -
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. -
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]