DICOM Support for Compression: More Than JPEG (MIIT 2009)
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Exploring the .BMP File Format
Exploring the .BMP File Format Don Lancaster Synergetics, Box 809, Thatcher, AZ 85552 copyright c2003 as GuruGram #14 http://www.tinaja.com [email protected] (928) 428-4073 The .BMP image standard is used by Windows and elsewhere to represent graphics images in any of several different display and compression options. The .BMP advantages are that each pixel is usually independently available for any alteration or modification. And that repeated use does not normally degrade the image. Because lossy compression is not used. Its main disadvantage is that file sizes are usually horrendous compared to JPEG, fractal, GIF, or other lossy compression schemes. A comparison of popular image standards can be found here. I’ve long been using the .BMP format for my eBay and my other phototography, scanning, and post processing. I firmly believe that… All photography, scanning, and all image post-processing should always be done using .BMP or a similar non-lossy format. Only after all post-processing is complete should JPEG or another compressed distribution format be chosen. Some current examples of my .BMP work now do include the IMAGIMAG.PDF post-processing tutorial, the Bitmap Typewriterthat generates fully anti-aliased small fonts, the Aerial Photo Combiner, and similar utilities and tutorials found on our Fonts & Images, PostScript, and on our Acrobat library pages. A few projects of current interest involving .BMP files include true view camera swings and tilts for a digital camera, distortion correction, dodging & burning, preventing white punchthrough on knockouts, and emphasis vignetting. Mainly applied to uncompressed RGBX 24-bit color .BMP files. -
PDF/A for Scanned Documents
Webinar www.pdfa.org PDF/A for Scanned Documents Paper Becomes Digital Mark McKinney, LuraTech, Inc., President Armin Ortmann, LuraTech, CTO Mark McKinney President, LuraTech, Inc. © 2009 PDF/A Competence Center, www.pdfa.org Existing Solutions for Scanned Documents www.pdfa.org Black & White: TIFF G4 Color: Mostly JPEG, but sometimes PNG, BMP and other raster graphics formats Often special version formats like “JPEG in TIFF” Disadvantages: Several formats already for scanned documents Even more formats for born digital documents Loss of information, e.g. with TIFF G4 Bad image quality and huge file size, e.g. with JPEG No standardized metadata spread over all formats Not full text searchable (OCR) inside of files Black/White: Color: - TIFF FAX G4 - TIFF - TIFF LZW Mark McKinney - JPEG President, LuraTech, Inc. - PDF 2 Existing Solutions for Scanned Documents www.pdfa.org Bad image quality vs. file size TIFF/BMP JPEG TIFF G4 23.8 MB 180 kB 60 kB Mark McKinney President, LuraTech, Inc. 3 Alternative Solution: PDF www.pdfa.org PDF is already widely used to: Unify file formats Image à PDF “Office” Documents à PDF Other sources à PDF Create full-text searchable files Apply modern compression technology (e.g. the JPEG2000 file formats family) Harmonize metadata Conclusion: PDF avoids the disadvantages of the legacy formats “So if you are already using PDF as archival Mark McKinney format, why not use PDF/A with its many President, LuraTech, Inc. advantages?” 4 PDF/A www.pdfa.org What is PDF/A? • ISO 19005-1, Document Management • Electronic document file format for long-term preservation Goals of PDF/A: • Maintain static visual representation of documents • Consistent handing of Metadata • Option to maintain structure and semantic meaning of content • Transparency to guarantee access • Limit the number of restrictions Mark McKinney President, LuraTech, Inc. -
TS 101 499 V2.2.1 (2008-07) Technical Specification
ETSI TS 101 499 V2.2.1 (2008-07) Technical Specification Digital Audio Broadcasting (DAB); MOT SlideShow; User Application Specification European Broadcasting Union Union Européenne de Radio-Télévision EBU·UER 2 ETSI TS 101 499 V2.2.1 (2008-07) Reference RTS/JTC-DAB-57 Keywords audio, broadcasting, DAB, digital, PAD ETSI 650 Route des Lucioles F-06921 Sophia Antipolis Cedex - FRANCE Tel.: +33 4 92 94 42 00 Fax: +33 4 93 65 47 16 Siret N° 348 623 562 00017 - NAF 742 C Association à but non lucratif enregistrée à la Sous-Préfecture de Grasse (06) N° 7803/88 Important notice Individual copies of the present document can be downloaded from: http://www.etsi.org The present document may be made available in more than one electronic version or in print. In any case of existing or perceived difference in contents between such versions, the reference version is the Portable Document Format (PDF). In case of dispute, the reference shall be the printing on ETSI printers of the PDF version kept on a specific network drive within ETSI Secretariat. Users of the present document should be aware that the document may be subject to revision or change of status. Information on the current status of this and other ETSI documents is available at http://portal.etsi.org/tb/status/status.asp If you find errors in the present document, please send your comment to one of the following services: http://portal.etsi.org/chaircor/ETSI_support.asp Copyright Notification No part may be reproduced except as authorized by written permission. -
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. -
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 -
51 Document Output
◆ Document Output <Function> You can output a document from “Document List” as an image file. All the documents selected in “Document List” can be outputted as a document in a specified format. <ICP Setting Procedures> Refer to 4 3, 6 15 1. Click “Output Document” at the right side. 2. The “Save As” dialog box appears. 3. Click “Compression” to confirm the file compression setting for “TIFF File”. If you change, click “OK”. 4. Select “PDF File” as a file format in the “Save as type” list box. 5. Click “Compression” to confirm the file compression setting for “PDF File”. If you change, click “OK”. 6. Select “PDF(Searchable) File” as a file format in the “Save as type” list box. 7. Click “OCR Settings” to confirm the searchable file setting. If you change, click “OK”. 8. Select “Jpeg File” as a file format in the “Save as type” list box. 9. Click “Compression” to confirm the file compression setting for “JPEG File”. If you change, click “OK”. 10. Select “Jpeg2000 File” as a file format in the “Save as type” list box. 11. Click “Compression” to confirm the file compression setting for “Jpeg2000 File”. If you change, click “OK”. 12. Select “Depends on Image Type” in the “Save as type” list box. 13. “File Type Settings” dialog box appears and confirm the settings for each type. If you change, click “OK”. 14. Select “Jpeg File” as a file format in the “Save as type” list box. 15. Confirm the setting of File Name at the bottom right and click “Save”. -
(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 -
Chapter 9 Image Compression Standards
Fundamentals of Multimedia, Chapter 9 Chapter 9 Image Compression Standards 9.1 The JPEG Standard 9.2 The JPEG2000 Standard 9.3 The JPEG-LS Standard 9.4 Bi-level Image Compression Standards 9.5 Further Exploration 1 Li & Drew c Prentice Hall 2003 ! Fundamentals of Multimedia, Chapter 9 9.1 The JPEG Standard JPEG is an image compression standard that was developed • by the “Joint Photographic Experts Group”. JPEG was for- mally accepted as an international standard in 1992. JPEG is a lossy image compression method. It employs a • transform coding method using the DCT (Discrete Cosine Transform). An image is a function of i and j (or conventionally x and y) • in the spatial domain. The 2D DCT is used as one step in JPEG in order to yield a frequency response which is a function F (u, v) in the spatial frequency domain, indexed by two integers u and v. 2 Li & Drew c Prentice Hall 2003 ! Fundamentals of Multimedia, Chapter 9 Observations for JPEG Image Compression The effectiveness of the DCT transform coding method in • JPEG relies on 3 major observations: Observation 1: Useful image contents change relatively slowly across the image, i.e., it is unusual for intensity values to vary widely several times in a small area, for example, within an 8 8 × image block. much of the information in an image is repeated, hence “spa- • tial redundancy”. 3 Li & Drew c Prentice Hall 2003 ! Fundamentals of Multimedia, Chapter 9 Observations for JPEG Image Compression (cont’d) Observation 2: Psychophysical experiments suggest that hu- mans are much less likely to notice the loss of very high spatial frequency components than the loss of lower frequency compo- nents. -
Preparation Method for TIFF File (*.Tif) Over 300Dpi
Preparation method for TIFF file (*.tif) over 300dpi Using software with saving function of TIFF file. (e.g. DeltaGraph) 1. Select the figure. 2. On the “File” menu, point to “Export”, and then select “Image”. 3. Click “Option”, and select “Color/Gray-scale”. 4. Select “TIFF” in the “File type” dialog box, and save the file at over “300”dpi. Using Microsoft Excel. A) Using draw type graphics software. (e.g. Illustrator, Canvas, etc.) 1. Select the figure in Excel. 2. Copy the figure and paste into graphics software. 3. On the “File” menu, point to “Save as”, and save the file after select “TIFF (over 300dpi)“ in the “File type” dialog box. Compression “LZW”, “ZIP”, or “JPEG” should be used in compression mode for TIFF file to reduce the file size. B) Simple method Color printing by Excel or PowerPoint graphics 1. Select the figure in Excel or PowerPoint. 2. On the “File” menu, point to “Print”, and select “Microsoft Office Document Image Writer” under “printer”. Click “Properties”, click the “Advanced” tab, and then check “MDI” under “Output format”. 3. Click “OK”、and then close the “Properties”. 4. Click “OK” under “printer” and save the MDI file. 5. Start Windows Explorer. 6. Open the saved MDI file, or right-click of the saved MDI file —in the “Open with” dialog box; click “Microsoft Office Document Imaging”. 7. On the “Tool” menu, point to “Option”. In the “Compression” tab, check “LZW”, and then click “OK”. 8. On the “File” menu, point to “Save as”, and then select “TIFF ” in the “File type” dialog box. -
Lossy Image Compression Based on Prediction Error and Vector Quantisation Mohamed Uvaze Ahamed Ayoobkhan* , Eswaran Chikkannan and Kannan Ramakrishnan
Ayoobkhan et al. EURASIP Journal on Image and Video Processing (2017) 2017:35 EURASIP Journal on Image DOI 10.1186/s13640-017-0184-3 and Video Processing RESEARCH Open Access Lossy image compression based on prediction error and vector quantisation Mohamed Uvaze Ahamed Ayoobkhan* , Eswaran Chikkannan and Kannan Ramakrishnan Abstract Lossy image compression has been gaining importance in recent years due to the enormous increase in the volume of image data employed for Internet and other applications. In a lossy compression, it is essential to ensure that the compression process does not affect the quality of the image adversely. The performance of a lossy compression algorithm is evaluated based on two conflicting parameters, namely, compression ratio and image quality which is usually measured by PSNR values. In this paper, a new lossy compression method denoted as PE-VQ method is proposed which employs prediction error and vector quantization (VQ) concepts. An optimum codebook is generated by using a combination of two algorithms, namely, artificial bee colony and genetic algorithms. The performance of the proposed PE-VQ method is evaluated in terms of compression ratio (CR) and PSNR values using three different types of databases, namely, CLEF med 2009, Corel 1 k and standard images (Lena, Barbara etc.). Experiments are conducted for different codebook sizes and for different CR values. The results show that for a given CR, the proposed PE-VQ technique yields higher PSNR value compared to the existing algorithms. It is also shown that higher PSNR values can be obtained by applying VQ on prediction errors rather than on the original image pixels. -
Understanding Image Formats and When to Use Them
Understanding Image Formats And When to Use Them Are you familiar with the extensions after your images? There are so many image formats that it’s so easy to get confused! File extensions like .jpeg, .bmp, .gif, and more can be seen after an image’s file name. Most of us disregard it, thinking there is no significance regarding these image formats. These are all different and not cross‐ compatible. These image formats have their own pros and cons. They were created for specific, yet different purposes. What’s the difference, and when is each format appropriate to use? Every graphic you see online is an image file. Most everything you see printed on paper, plastic or a t‐shirt came from an image file. These files come in a variety of formats, and each is optimized for a specific use. Using the right type for the right job means your design will come out picture perfect and just how you intended. The wrong format could mean a bad print or a poor web image, a giant download or a missing graphic in an email Most image files fit into one of two general categories—raster files and vector files—and each category has its own specific uses. This breakdown isn’t perfect. For example, certain formats can actually contain elements of both types. But this is a good place to start when thinking about which format to use for your projects. Raster Images Raster images are made up of a set grid of dots called pixels where each pixel is assigned a color. -
Image Compression Using Discrete Cosine Transform Method
Qusay Kanaan Kadhim, International Journal of Computer Science and Mobile Computing, Vol.5 Issue.9, September- 2016, pg. 186-192 Available Online at www.ijcsmc.com International Journal of Computer Science and Mobile Computing A Monthly Journal of Computer Science and Information Technology ISSN 2320–088X IMPACT FACTOR: 5.258 IJCSMC, Vol. 5, Issue. 9, September 2016, pg.186 – 192 Image Compression Using Discrete Cosine Transform Method Qusay Kanaan Kadhim Al-Yarmook University College / Computer Science Department, Iraq [email protected] ABSTRACT: The processing of digital images took a wide importance in the knowledge field in the last decades ago due to the rapid development in the communication techniques and the need to find and develop methods assist in enhancing and exploiting the image information. The field of digital images compression becomes an important field of digital images processing fields due to the need to exploit the available storage space as much as possible and reduce the time required to transmit the image. Baseline JPEG Standard technique is used in compression of images with 8-bit color depth. Basically, this scheme consists of seven operations which are the sampling, the partitioning, the transform, the quantization, the entropy coding and Huffman coding. First, the sampling process is used to reduce the size of the image and the number bits required to represent it. Next, the partitioning process is applied to the image to get (8×8) image block. Then, the discrete cosine transform is used to transform the image block data from spatial domain to frequency domain to make the data easy to process.