An Analysis of Compression Methods and Implementation of Medical
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Information and Compression Introduction Summary of Course
Information and compression Introduction ■ We will be looking at what information is Information and Compression ■ Methods of measuring it ■ The idea of compression ■ 2 distinct ways of compressing images Paul Cockshott Faraday partnership Summary of Course Agenda ■ At the end of this lecture you should have ■ Encoding systems an idea what information is, its relation to ■ BCD versus decimal order, and why data compression is possible ■ Information efficiency ■ Shannons Measure ■ Chaitin, Kolmogorov Complexity Theory ■ Relation to Goedels theorem Overview Connections ■ Data coms channels bounded ■ Simple encoding example shows different ■ Images take great deal of information in raw densities possible form ■ Shannons information theory deals with ■ Efficient transmission requires denser transmission encoding ■ Chaitin relates this to Turing machines and ■ This requires that we understand what computability information actually is ■ Goedels theorem limits what we know about compression paul 1 Information and compression Vocabulary What is information ■ information, ■ Information measured in bits ■ entropy, ■ Bit equivalent to binary digit ■ compression, ■ Why use binary system not decimal? ■ redundancy, ■ Decimal would seem more natural ■ lossless encoding, ■ Alternatively why not use e, base of natural ■ lossy encoding logarithms instead of 2 or 10 ? Voltage encoding Noise Immunity Binary voltage ■ ■ ■ 5v Digital information BINARY DECIMAL encoded as ranges of ■ 2 values 0,1 ■ 10 values 0..9 continuous variables 1 ■ 1 isolation band ■ -
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. -
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. -
An Improved Fast Fractal Image Compression Coding Method
Rev. Téc. Ing. Univ. Zulia. Vol. 39, Nº 9, 241 - 247, 2016 doi:10.21311/001.39.9.32 An Improved Fast Fractal Image Compression Coding Method Haibo Gao, Wenjuan Zeng, Jifeng Chen, Cheng Zhang College of Information Science and Engineering, Hunan International Economics University, Changsha 410205, Hunan, China Abstract The main purpose of image compression is to use as many bits as possible to represent the source image by eliminating the image redundancy with acceptable restoration. Fractal image compression coding has achieved good results in the field of image compression due to its high compression ratio, fast decoding speed as well as independency between decoding image and resolution. However, there is a big problem in this method, i.e. long coding time because there are considerable searches of fractal blocks in the coding. Based on the theoretical foundation of fractal coding and fractal compression algorithm, this paper researches every step of this compression method, including block partition, block search and the representation of affine transformation coefficient, in order to come up with optimization and improvement strategies. The simulation result shows that the algorithm of this paper can achieve excellent effects in coding time and compression ratio while ensuring better image quality. The work on fractal coding in this paper has made certain contributions to the research of fractal coding. Key words: Image Compression, Fractal Theory, Coding and Decoding. 1. INTRODUCTION Image compression is aimed to use as many bytes as possible to represent and transmit the original big image and to have a better quality in the restored image. -
How to Exploit the Transferability of Learned Image Compression to Conventional Codecs
How to Exploit the Transferability of Learned Image Compression to Conventional Codecs Jan P. Klopp Keng-Chi Liu National Taiwan University Taiwan AI Labs [email protected] [email protected] Liang-Gee Chen Shao-Yi Chien National Taiwan University [email protected] [email protected] Abstract Lossy compression optimises the objective Lossy image compression is often limited by the sim- L = R + λD (1) plicity of the chosen loss measure. Recent research sug- gests that generative adversarial networks have the ability where R and D stand for rate and distortion, respectively, to overcome this limitation and serve as a multi-modal loss, and λ controls their weight relative to each other. In prac- especially for textures. Together with learned image com- tice, computational efficiency is another constraint as at pression, these two techniques can be used to great effect least the decoder needs to process high resolutions in real- when relaxing the commonly employed tight measures of time under a limited power envelope, typically necessitating distortion. However, convolutional neural network-based dedicated hardware implementations. Requirements for the algorithms have a large computational footprint. Ideally, encoder are more relaxed, often allowing even offline en- an existing conventional codec should stay in place, ensur- coding without demanding real-time capability. ing faster adoption and adherence to a balanced computa- Recent research has developed along two lines: evolu- tional envelope. tion of exiting coding technologies, such as H264 [41] or As a possible avenue to this goal, we propose and investi- H265 [35], culminating in the most recent AV1 codec, on gate how learned image coding can be used as a surrogate the one hand. -
Download Media Player Codec Pack Version 4.1 Media Player Codec Pack
download media player codec pack version 4.1 Media Player Codec Pack. Description: In Microsoft Windows 10 it is not possible to set all file associations using an installer. Microsoft chose to block changes of file associations with the introduction of their Zune players. Third party codecs are also blocked in some instances, preventing some files from playing in the Zune players. A simple workaround for this problem is to switch playback of video and music files to Windows Media Player manually. In start menu click on the "Settings". In the "Windows Settings" window click on "System". On the "System" pane click on "Default apps". On the "Choose default applications" pane click on "Films & TV" under "Video Player". On the "Choose an application" pop up menu click on "Windows Media Player" to set Windows Media Player as the default player for video files. Footnote: The same method can be used to apply file associations for music, by simply clicking on "Groove Music" under "Media Player" instead of changing Video Player in step 4. Media Player Codec Pack Plus. Codec's Explained: A codec is a piece of software on either a device or computer capable of encoding and/or decoding video and/or audio data from files, streams and broadcasts. The word Codec is a portmanteau of ' co mpressor- dec ompressor' Compression types that you will be able to play include: x264 | x265 | h.265 | HEVC | 10bit x265 | 10bit x264 | AVCHD | AVC DivX | XviD | MP4 | MPEG4 | MPEG2 and many more. File types you will be able to play include: .bdmv | .evo | .hevc | .mkv | .avi | .flv | .webm | .mp4 | .m4v | .m4a | .ts | .ogm .ac3 | .dts | .alac | .flac | .ape | .aac | .ogg | .ofr | .mpc | .3gp and many more. -
2018-07-11 and for Information to the Iso Member Bodies and to the Tmb Members
Sergio Mujica Secretary-General TO THE CHAIRS AND SECRETARIES OF ISO COMMITTEES 2018-07-11 AND FOR INFORMATION TO THE ISO MEMBER BODIES AND TO THE TMB MEMBERS ISO/IEC/ITU coordination – New work items Dear Sir or Madam, Please find attached the lists of IEC, ITU and ISO new work items issued in June 2018. If you wish more information about IEC technical committees and subcommittees, please access: http://www.iec.ch/. Click on the last option to the right: Advanced Search and then click on: Documents / Projects / Work Programme. In case of need, a copy of an actual IEC new work item may be obtained by contacting [email protected]. Please note for your information that in the annexed table from IEC the "document reference" 22F/188/NP means a new work item from IEC Committee 22, Subcommittee F. If you wish to look at the ISO new work items, please access: http://isotc.iso.org/pp/. On the ISO Project Portal you can find all information about the ISO projects, by committee, document number or project ID, or choose the option "Stages search" and select "Search" to obtain the annexed list of ISO new work items. Yours sincerely, Sergio Mujica Secretary-General Enclosures ISO New work items 1 of 8 2018-07-11 Alert Detailed alert Timeframe Reference Document title Developing committee VA Registration dCurrent stage Stage date Guidance for multiple organizations implementing a common Warning Warning – NP decision SDT 36 ISO/NP 50009 (ISO50001) EnMS ISO/TC 301 - - 10.60 2018-06-10 Warning Warning – NP decision SDT 36 ISO/NP 31050 Guidance for managing -
Completed Projects / Projets Terminés
Completed Projects / Projets terminés New Standards — New Editions — Special Publications Please note that the following standards were developed by the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC), and have been adopted by the Canadian Standards Association. These standards are available in PDF format only. CAN/CSA-ISO/IEC 2593:02, 4th edition Information Technology–Telecommunications and Information Exchange Between Systems–34-Pole DTE/DCE Interface Connector Mateability Dimensions and Contact Number Assignments (Adopted ISO/IEC 2593:2000).................................... $85 CAN/CSA-ISO/IEC 7811-2:02, 3rd edition Identification Cards–Recording Technique–Part 2: Magnetic Stripe–Low Coercivity (Adopted ISO/IEC 7811-2:2001) .................................................................................... $95 CAN/CSA-ISO/IEC 8208:02, 4th edition Information Technology–Data Communications–X.25 Packet Layer Protocol for Data Terminal Equipment (Adopted ISO/IEC 8208:2000) ............................................ $220 CAN/CSA-ISO/IEC 8802-3:02, 2nd edition Information Technology–Telecommunications and Information Exchange Between Systems–Local and Metropolitan Area Networks–Specific Requirements–Part 3: Carrier Sense Multiple Access with Collision Detection (CSMA/CD) Access Method and Physical Layer (Adopted ISO/IEC 8802-3:2000/IEEE Std 802.3, 2000) ................. $460 CAN/CSA-ISO/IEC 9798-1:02, 2nd edition Information Technology–Security Techniques–Entity Authentication–Part -
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. -
A Forensic Database for Digital Audio, Video, and Image Media
THE “DENVER MULTIMEDIA DATABASE”: A FORENSIC DATABASE FOR DIGITAL AUDIO, VIDEO, AND IMAGE MEDIA by CRAIG ANDREW JANSON B.A., University of Richmond, 1997 A thesis submitted to the Faculty of the Graduate School of the University of Colorado Denver in partial fulfillment of the requirements for the degree of Master of Science Recording Arts Program 2019 This thesis for the Master of Science degree by Craig Andrew Janson has been approved for the Recording Arts Program by Catalin Grigoras, Chair Jeff M. Smith Cole Whitecotton Date: May 18, 2019 ii Janson, Craig Andrew (M.S., Recording Arts Program) The “Denver Multimedia Database”: A Forensic Database for Digital Audio, Video, and Image Media Thesis directed by Associate Professor Catalin Grigoras ABSTRACT To date, there have been multiple databases developed for use in many forensic disciplines. There are very large and well-known databases like CODIS (DNA), IAFIS (fingerprints), and IBIS (ballistics). There are databases for paint, shoeprint, glass, and even ink; all of which catalog and maintain information on all the variations of their specific subject matter. Somewhat recently there was introduced the “Dresden Image Database” which is designed to provide a digital image database for forensic study and contains images that are generic in nature, royalty free, and created specifically for this database. However, a central repository is needed for the collection and study of digital audios, videos, and images. This kind of database would permit researchers, students, and investigators to explore the data from various media and various sources, compare an unknown with knowns with the possibility of discovering the likely source of the unknown. -
Lossless Data Compression with Transformer
Under review as a conference paper at ICLR 2020 LOSSLESS DATA COMPRESSION WITH TRANSFORMER Anonymous authors Paper under double-blind review ABSTRACT Transformers have replaced long-short term memory and other recurrent neural networks variants in sequence modeling. It achieves state-of-the-art performance on a wide range of tasks related to natural language processing, including lan- guage modeling, machine translation, and sentence representation. Lossless com- pression is another problem that can benefit from better sequence models. It is closely related to the problem of online learning of language models. But, despite this ressemblance, it is an area where purely neural network based methods have not yet reached the compression ratio of state-of-the-art algorithms. In this paper, we propose a Transformer based lossless compression method that match the best compression ratio for text. Our approach is purely based on neural networks and does not rely on hand-crafted features as other lossless compression algorithms. We also provide a thorough study of the impact of the different components of the Transformer and its training on the compression ratio. 1 INTRODUCTION Lossless compression is a class of compression algorithms that allows for the perfect reconstruc- tion of the original data. In the last decades, statistical methods for lossless compression have been dominated by PAQ-type approaches (Mahoney, 2005). The structure of these approaches is similar to the Prediction by Partial Matching (PPM) of Cleary & Witten (1984) and are composed of two separated parts: a predictor and an entropy encoding. Entropy coding scheme like arithmetic cod- ing (Rissanen & Langdon, 1979) are optimal and most of the compression gains are coming from improving the predictor. -
(L3) - Audio/Picture Coding
Committee: (L3) - Audio/Picture Coding National Designation Title (Click here to purchase standards) ISO/IEC Document L3 INCITS/ISO/IEC 9281-1:1990:[R2013] Information technology - Picture Coding Methods - Part 1: Identification IS 9281-1:1990 INCITS/ISO/IEC 9281-2:1990:[R2013] Information technology - Picture Coding Methods - Part 2: Procedure for Registration IS 9281-2:1990 INCITS/ISO/IEC 9282-1:1988:[R2013] Information technology - Coded Representation of Computer Graphics Images - Part IS 9282-1:1988 1: Encoding principles for picture representation in a 7-bit or 8-bit environment :[] Information technology - Coding of Multimedia and Hypermedia Information - Part 7: IS 13522-7:2001 Interoperability and conformance testing for ISO/IEC 13522-5 (MHEG-7) :[] Information technology - Coding of Multimedia and Hypermedia Information - Part 5: IS 13522-5:1997 Support for Base-Level Interactive Applications (MHEG-5) :[] Information technology - Coding of Multimedia and Hypermedia Information - Part 3: IS 13522-3:1997 MHEG script interchange representation (MHEG-3) :[] Information technology - Coding of Multimedia and Hypermedia Information - Part 6: IS 13522-6:1998 Support for enhanced interactive applications (MHEG-6) :[] Information technology - Coding of Multimedia and Hypermedia Information - Part 8: IS 13522-8:2001 XML notation for ISO/IEC 13522-5 (MHEG-8) Created: 11/16/2014 Page 1 of 44 Committee: (L3) - Audio/Picture Coding National Designation Title (Click here to purchase standards) ISO/IEC Document :[] Information technology - Coding