Designing and Developing a Model for Converting Image Formats Using Java API for Comparative Study of Different Image Formats
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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. -
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. -
Iriscompressor Software and to This Publication
User Guide Legal Notices ICOMP_Pro-dgi/pko-24012012-01 Copyrights Copyrights ©2011-2012 I.R.I.S. All Rights Reserved. I.R.I.S. owns the copyrights to the IRISCompressor software and to this publication. The information contained in this document is the property of I.R.I.S. Its content is subject to change without notice and does not represent a commitment on the part of I.R.I.S. The software described in this document is furnished under a license agreement which states the terms for use of this product. The software may be used or copied only in accordance with the terms of that agreement. No part of this publication may be reproduced, transmitted, stored in a retrieval system, or translated into another language without the prior written consent of I.R.I.S. Trademarks The I.R.I.S. logo and IRISCompressor are trademarks of I.R.I.S. OCR ("Optical Character Recognition"), IDR ("Intelligent Document Recognition") and iHQC ("intelligent High Quality Compression) technology by I.R.I.S. All other products mentioned in this publication are trademarks or registered trademarks of their respective owners. iHQCTM patent-protected. US Patent No. 8,068,684 B2. 1 INTRODUCTION IRISCompressor Pro is a handy compression tool that allows you to convert your image and PDF files into compressed PDF files in just a few mouse clicks. The PDF files IRISCompressor generates are fully text-searchable, thanks to I.R.I.S.' OCR technology (Optical Character Recognition). IMPORTANT NOTES IRISCompressor Pro can process multiple image and PDF files at a time. -
Panstamps Documentation Release V0.5.3
panstamps Documentation Release v0.5.3 Dave Young 2020 Getting Started 1 Installation 3 1.1 Troubleshooting on Mac OSX......................................3 1.2 Development...............................................3 1.2.1 Sublime Snippets........................................4 1.3 Issues...................................................4 2 Command-Line Usage 5 3 Documentation 7 4 Command-Line Tutorial 9 4.1 Command-Line..............................................9 4.1.1 JPEGS.............................................. 12 4.1.2 Temporal Constraints (Useful for Moving Objects)...................... 17 4.2 Importing to Your Own Python Script.................................. 18 5 Installation 19 5.1 Troubleshooting on Mac OSX...................................... 19 5.2 Development............................................... 19 5.2.1 Sublime Snippets........................................ 20 5.3 Issues................................................... 20 6 Command-Line Usage 21 7 Documentation 23 8 Command-Line Tutorial 25 8.1 Command-Line.............................................. 25 8.1.1 JPEGS.............................................. 28 8.1.2 Temporal Constraints (Useful for Moving Objects)...................... 33 8.2 Importing to Your Own Python Script.................................. 34 8.2.1 Subpackages.......................................... 35 8.2.1.1 panstamps.commonutils (subpackage)........................ 35 8.2.1.2 panstamps.image (subpackage)............................ 35 8.2.2 Classes............................................ -
Datasheet-Smartsignage
Fanless Embedded Box PC with Intel® Celeron® SmartSignage 4-core Processor J1900 EBC-3311 Features Fanless digital signage solution Cableless design Low power consumption 1 x USB 3.0 Line-out 1 x USB 2.0 2 x RJ-45 VGA DC INPUT 12V On board Intel® Celeron® 4-core Processor EBC-3311B High definition video output J1900 (Bay Trail) Supports DDR3L SO-DIMM 1333 max. up to 8GB 1 x High definition video output & 1 VGA or 2 x High definition video output 1 x USB 3.0 Line-out 1 x USB 2.0 2 x RJ-45 DC INPUT 12V Front Side 1 mSATA supported High definition video output Supports VESA mount Rear Side Power Switch Applications Digital Signage Kiosk Engine POS PC IoT Gateway Specifications Image format Jpeg, tiff, png, (anim) gif, bmp System Optional for 802.11 b/g/n CPU Intel® Celeron® 4-core Processor J1900 WiFi (Bay Trail) Expansion Slot 1 x full-size Mini card Chipset SoC integrated (for mSATA) System Memory 1 x DDR3L 1333 max up to 8GB 1 x half-size PCI Express Mini card Storage 1 x mSATA supported for optional WiFi module Watchdog Timer 255 levels, 1-255 sec. Power Supply 12V DC-in I/O 1 x USB 2.0 , 1 x USB 3.0 2 x 10/100/1000Mbps Ethernet Dimensions (W x D x H) 170 x 120 x 40 mm 1 x power on/off button 6.69 x 4.72 x 1.57” 1 x Audio (Line-out) Packing Dimension 320 x 205 x 65 mm Video I/O EBC-3311 EBC-3311B (W x D x H) 12.59 x 8.07 x 2.55” 1 x High 2 x High definition Weight (net/gross) 0.7kg(1.5lb)/1.2kg(2.61b) definition video output video output Environmental 1 x VGA Operation Temperature 0°C – +40°C,(32°F – 104°F) Video MPEG-4, MPEG-2, MPEG-1, H.264, -
Autodesk White Paper
AUTOCAD RASTER DESIGN 2010 FEATURES AND BENEFITS AutoCAD® Raster Design 2010 Features and Benefits Make the most of rasterized scanned drawings, maps, aerial photos, satellite imagery, and digital elevation models. Get more out of your raster data and enhance your designs, plans, presentations, ® and maps with AutoCAD Raster Design software. Contents Introduction ...................................................................................................................... 2 New Features and Enhancements .................................................................................. 2 Image Display ................................................................................................................... 3 Image Editing and Cleanup ............................................................................................. 4 Vectorization Tools with SmartCorrect .......................................................................... 6 Raster Entity Manipulation (REM) with SmartPick ....................................................... 7 Georeferenced Image Display and Analysis .................................................................. 8 Image Transformations .................................................................................................. 10 www.autodesk.com/rasterdesign AUTOCAD RASTER DESIGN 2010 FEATURES AND BENEFITS Introduction Extend the power of AutoCAD® and AutoCAD-based software by using AutoCAD Raster Design software for a wide range of applications. Get more out of your raster -
Design and Implementation of Image Processing and Compression Algorithms for a Miniature Embedded Eye Tracking System Pavel Morozkin
Design and implementation of image processing and compression algorithms for a miniature embedded eye tracking system Pavel Morozkin To cite this version: Pavel Morozkin. Design and implementation of image processing and compression algorithms for a miniature embedded eye tracking system. Signal and Image processing. Sorbonne Université, 2018. English. NNT : 2018SORUS435. tel-02953072 HAL Id: tel-02953072 https://tel.archives-ouvertes.fr/tel-02953072 Submitted on 29 Sep 2020 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Sorbonne Université Institut supérieur d’électronique de Paris (ISEP) École doctorale : « Informatique, télécommunications & électronique de Paris » Design and Implementation of Image Processing and Compression Algorithms for a Miniature Embedded Eye Tracking System Par Pavel MOROZKIN Thèse de doctorat de Traitement du signal et de l’image Présentée et soutenue publiquement le 29 juin 2018 Devant le jury composé de : M. Ales PROCHAZKA Rapporteur M. François-Xavier COUDOUX Rapporteur M. Basarab MATEI Examinateur M. Habib MEHREZ Examinateur Mme Maria TROCAN Directrice de thèse M. Marc Winoc SWYNGHEDAUW Encadrant Abstract Human-Machine Interaction (HMI) progressively becomes a part of coming future. Being an example of HMI, embedded eye tracking systems allow user to interact with objects placed in a known environment by using natural eye movements. -
Making Color Images with the GIMP Las Cumbres Observatory Global Telescope Network Color Imaging: the GIMP Introduction
Las Cumbres Observatory Global Telescope Network Making Color Images with The GIMP Las Cumbres Observatory Global Telescope Network Color Imaging: The GIMP Introduction These instructions will explain how to use The GIMP to take those three images and composite them to make a color image. Users will also learn how to deal with minor imperfections in their images. Note: The GIMP cannot handle FITS files effectively, so to produce a color image, users will have needed to process FITS files and saved them as grayscale TIFF or JPEG files as outlined in the Basic Imaging section. Separately filtered FITS files are available for you to use on the Color Imaging page. The GIMP can be downloaded for Windows, Mac, and Linux from: www.gimp.org Loading Images Loading TIFF/JPEG Files Users will be processing three separate images to make the RGB color images. When opening files in The GIMP, you can select multiple files at once by holding the Ctrl button and clicking on the TIFF or JPEG files you wish to use to make a color image. Go to File > Open. Image Mode RGB Mode Because these images are saved as grayscale, all three images need to be converted to RGB. This is because color images are made from (R)ed, (G)reen, and (B)lue picture elements (pixels). The different shades of gray in the image show the intensity of light in each of the wavelengths through the red, green, and blue filters. The colors themselves are not recorded in the image. Adding Color Information For the moment, these images are just grayscale. -
Openimageio 1.7 Programmer Documentation (In Progress)
OpenImageIO 1.7 Programmer Documentation (in progress) Editor: Larry Gritz [email protected] Date: 31 Mar 2016 ii The OpenImageIO source code and documentation are: Copyright (c) 2008-2016 Larry Gritz, et al. All Rights Reserved. The code that implements OpenImageIO is licensed under the BSD 3-clause (also some- times known as “new BSD” or “modified BSD”) license: Redistribution and use in source and binary forms, with or without modification, are per- mitted provided that the following conditions are met: • Redistributions of source code must retain the above copyright notice, this list of condi- tions and the following disclaimer. • Redistributions in binary form must reproduce the above copyright notice, this list of con- ditions and the following disclaimer in the documentation and/or other materials provided with the distribution. • Neither the name of the software’s owners nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIB- UTORS ”AS IS” AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FIT- NESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUD- ING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABIL- ITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. -
Dynamic Resource Management of Network-On-Chip Platforms for Multi-Stream Video Processing
DYNAMIC RESOURCE MANAGEMENT OF NETWORK-ON-CHIP PLATFORMS FOR MULTI-STREAM VIDEO PROCESSING Hashan Roshantha Mendis Doctor of Engineering University of York Computer Science March 2017 2 Abstract This thesis considers resource management in the context of parallel multiple video stream de- coding, on multicore/many-core platforms. Such platforms have tens or hundreds of on-chip processing elements which are connected via a Network-on-Chip (NoC). Inefficient task allo- cation configurations can negatively affect the communication cost and resource contention in the platform, leading to predictability and performance issues. Efficient resource management for large-scale complex workloads is considered a challenging research problem; especially when applications such as video streaming and decoding have dynamic and unpredictable workload characteristics. For these type of applications, runtime heuristic-based task mapping techniques are required. As the application and platform size increase, decentralised resource management techniques are more desirable to overcome the reliability and performance bot- tlenecks in centralised management. In this work, several heuristic-based runtime resource management techniques, targeting real-time video decoding workloads are proposed. Firstly, two admission control approaches are proposed; one fully deterministic and highly predictable; the other is heuristic-based, which balances predictability and performance. Secondly, a pair of runtime task mapping schemes are presented, which make use of limited known application properties, communication cost and blocking-aware heuristics. Combined with the proposed deterministic admission con- troller, these techniques can provide strict timing guarantees for hard real-time streams whilst improving resource usage. The third contribution in this thesis is a distributed, bio-inspired, low-overhead, task re-allocation technique, which is used to further improve the timeliness and workload distribution of admitted soft real-time streams. -
Chapter 3 Image Data Representations
Chapter 3 Image Data Representations 1 IT342 Fundamentals of Multimedia, Chapter 3 Outline • Image data types: • Binary image (1-bit image) • Gray-level image (8-bit image) • Color image (8-bit and 24-bit images) • Image file formats: • GIF, JPEG, PNG, TIFF, EXIF 2 IT342 Fundamentals of Multimedia, Chapter 3 Graphics and Image Data Types • The number of file formats used in multimedia continues to proliferate. For example, Table 3.1 shows a list of some file formats used in the popular product Macromedia Director. Table 3.1: Macromedia Director File Formats File Import File Export Native Image Palette Sound Video Anim. Image Video .BMP, .DIB, .PAL .AIFF .AVI .DIR .BMP .AVI .DIR .GIF, .JPG, .ACT .AU .MOV .FLA .MOV .DXR .PICT, .PNG, .MP3 .FLC .EXE .PNT, .PSD, .WAV .FLI .TGA, .TIFF, .GIF .WMF .PPT 3 IT342 Fundamentals of Multimedia, Chapter 3 1-bit Image - binary image • Each pixel is stored as a single bit (0 or 1), so also referred to as binary image. • Such an image is also called a 1-bit monochrome image since it contains no color. It is satisfactory for pictures containing only simple graphics and text. • A 640X480 monochrome image requires 38.4 kilobytes of storage (= 640x480 / (8x1000)). 4 IT342 Fundamentals of Multimedia, Chapter 3 8-bit Gray-level Images • Each pixel has a gray-value between 0 and 255. Each pixel is represented by a single byte; e.g., a dark pixel might have a value of 10, and a bright one might be 230. • Bitmap: The two-dimensional array of pixel values that represents the graphics/image data. -
Institute for Clinical and Economic Review
INSTITUTE FOR CLINICAL AND ECONOMIC REVIEW FINAL APPRAISAL DOCUMENT CORONARY COMPUTED TOMOGRAPHIC ANGIOGRAPHY FOR DETECTION OF CORONARY ARTERY DISEASE January 9, 2009 Senior Staff Daniel A. Ollendorf, MPH, ARM Chief Review Officer Alexander Göhler, MD, PhD, MSc, MPH Lead Decision Scientist Steven D. Pearson, MD, MSc President, ICER Associate Staff Michelle Kuba, MPH Sr. Technology Analyst Marie Jaeger, B.S. Asst. Decision Scientist © 2009, Institute for Clinical and Economic Review 1 CONTENTS About ICER .................................................................................................................................. 3 Acknowledgments ...................................................................................................................... 4 Executive Summary .................................................................................................................... 5 Evidence Review Group Deliberation.................................................................................. 17 ICER Integrated Evidence Rating.......................................................................................... 25 Evidence Review Group Members........................................................................................ 27 Appraisal Overview.................................................................................................................. 30 Background ................................................................................................................................ 33