An Application for the Comparison of Lossless Still Image Compression Algorithms
Total Page:16
File Type:pdf, Size:1020Kb
Load more
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. -
Supported File Types
MyFax Supported File Formats Document Type Versions Extensions Adobe Portable Document Format (PDF) All Versions PDF Adobe Postscript All Versions PS Adobe Photoshop v. 3.0 and above PSD Amiga Interchange File Format (IFF) Raster Bitmap only IFF CAD Drawing Exchange Format (DXF) All AutoCad compatible versions DXF Comma Separated Values Format All Versions CSV Compuserve Graphics Interchange Format GIF87a, GIF89a GIF Corel Presentations Slide Show v. 96 and above SHW Corel Word Perfect v. 5.x. 6, 7, 8, 9 WPD, WP5, WP6 Encapsulated Postscript All Versions EPS Hypertext Markup Language HTML only with base href tag required HTML, HTM JPEG Joint Photography Experts Group All Versions JPG, JPEG Lotus 1-2-3 v. 2, 3, 4, 5, 96, 97, 9.x 123, WK1, WK3, WK4 Lotus Word Pro v. 96, 97, 9.x LWP Microsoft Excel v. 5, 95, 97, 2000, 2003, 2007 XLS, XLSX Microsoft PowerPoint v. 4 and above PPT, PPTX Microsoft Publisher v. 98, 2000, 2002, 2003, 2007 PUB Microsoft Windows Write All Versions WRI Microsoft Word Win: v. 97, 2000, 2003, 2007 Mac: v. 4, 5.x, 95, 98 DOC, DOCX Microsoft Word Template Win: v. 97, 2000, 2003, 2007 Mac: v. 4, 5.x, 95, 98 DOT, DOTX Microsoft Works Word Processor v. 4.x, 5, 6, 7, 8.x, 9 WPS OpenDocument Drawing All Versions ODG OpenDocument Presentation All Versions ODP OpenDocument Spreadsheet All Versions ODS OpenDocument Text All Versions ODT PC Paintbrush Graphics (PCX) All Versions PCX Plain Text All Versions TXT, DOC, LOG, ERR, C, CPP, H Portable Network Graphics (PNG) All Versions PNG Quattro Pro v. -
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. -
Imecom Print-2-Image Conversion Driver
IMECOM PRINT-2-IMAGE CONVERSION DRIVER Conve rt any document or file into high-quality TIFF, PDF, JPG, GIF, BMP, PCX, and DCX im age formats quickly and easily using Print-2-Image. DATASHEET OVERVIEW ABOUT IMECOM GROUP Print-2-Image™ enables you to convert any printable document or file into a high- quality image with ease. Using Print-2-Image, you can render files from any desktop Imecom Group began developing and or server-based application to various image formats simply by printing to Print-2- selling fax server software and image Image. If you can print it, Print-2-Image can convert it! conversion/printer driver software in 1989. Headquartered in New Hampshire, Print-2-Image has multiple image printer drivers built-in which enable you to Imecom Group presently supports over create high-quality image files in the format you desire. 12,000 solutions in 62+ countries, and we're growing fast. As we continue to • TIFF Printer Driver reach new technology levels, one thing • PDF Printer Driver remains constant: excellent customer support. Imecom Group maintains the • JPG Printer Driver highest quality level of customer support • GIF Printer Driver services in our market. It is one of the • BMP Printer Driver many reasons companies such as Alticor, Sears, Cigna, Johnson & Johnson • PCX Printer Driver Healthcare, Cerner, and others choose to • DCX Printer Driver implement our technology. We do not, and will not, forget that it is our customers All printer drivers are embedded within Print-2-Image to create a single solution for who help us be successful. -
Download This PDF File
Sindh Univ. Res. Jour. (Sci. Ser.) Vol.47 (3) 531-534 (2015) I NDH NIVERSITY ESEARCH OURNAL ( CIENCE ERIES) S U R J S S Performance Analysis of Image Compression Standards with Reference to JPEG 2000 N. MINALLAH++, A. KHALIL, M. YOUNAS, M. FURQAN, M. M. BOKHARI Department of Computer Systems Engineering, University of Engineering and Technology, Peshawar Received 12thJune 2014 and Revised 8th September 2015 Abstract: JPEG 2000 is the most widely used standard for still image coding. Some other well-known image coding techniques include JPEG, JPEG XR and WEBP. This paper provides performance evaluation of JPEG 2000 with reference to other image coding standards, such as JPEG, JPEG XR and WEBP. For the performance evaluation of JPEG 2000 with reference to JPEG, JPEG XR and WebP, we considered divers image coding scenarios such as continuous tome images, grey scale images, High Definition (HD) images, true color images and web images. Each of the considered algorithms are briefly explained followed by their performance evaluation using different quality metrics, such as Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), Structure Similarity Index (SSIM), Bits Per Pixel (BPP), Compression Ratio (CR) and Encoding/ Decoding Complexity. The results obtained showed that choice of the each algorithm depends upon the imaging scenario and it was found that JPEG 2000 supports the widest set of features among the evaluated standards and better performance. Keywords: Analysis, Standards JPEG 2000. performance analysis, followed by Section 6 with 1. INTRODUCTION There are different standards of image compression explanation of the considered performance analysis and decompression. -
Neural Multi-Scale Image Compression
Neural Multi-scale Image Compression Ken Nakanishi 1 Shin-ichi Maeda 2 Takeru Miyato 2 Daisuke Okanohara 2 Abstract 1.00 This study presents a new lossy image compres- sion method that utilizes the multi-scale features 0.98 of natural images. Our model consists of two networks: multi-scale lossy autoencoder and par- 0.96 allel multi-scale lossless coder. The multi-scale Proposed 0.94 JPEG lossy autoencoder extracts the multi-scale image MS-SSIM WebP features to quantized variables and the parallel BPG 0.92 multi-scale lossless coder enables rapid and ac- Johnston et al. Rippel & Bourdev curate lossless coding of the quantized variables 0.90 via encoding/decoding the variables in parallel. 0.0 0.2 0.4 0.6 0.8 1.0 Our proposed model achieves comparable perfor- Bits per pixel mance to the state-of-the-art model on Kodak and RAISE-1k dataset images, and it encodes a PNG image of size 768 × 512 in 70 ms with a single Figure 1. Rate-distortion trade off curves with different methods GPU and a single CPU process and decodes it on Kodak dataset. The horizontal axis represents bits-per-pixel into a high-fidelity image in approximately 200 (bpp) and the vertical axis represents multi-scale structural similar- ms. ity (MS-SSIM). Our model achieves better or comparable bpp with respect to the state-of-the-art results (Rippel & Bourdev, 2017). 1. Introduction K Data compression for video and image data is a crucial tech- via ML algorithm is not new. The -means algorithm was nique for reducing communication traffic and saving data used for vector quantization (Gersho & Gray, 2012), and storage. -
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. -
Multi-Media Imager Horizon ® G1 Multi-Media Imager
Hori zon ® G1 Multi-media Imager Horizon ® G1 Multi-media Imager Ove rview The Horizon G1 is an intelligent, desktop dry imager that produces diagnostic quality medical films plus grayscale paper prints if you choose the optional paper feature. The imager is compatible with many industry standard protocols including DICOM and Windows network printing. Horizon also features direct modality connection, with up to 24 simultaneous DICOM connections . High speed image processing, Optional A, A4 ,14”x17” 8” x10”, 14” x17” 11” x 14” Grayscale Pape r Blue and Clear Film Blue Film networking and spooling are standard. Speci fica tions Print Technology: Direct thermal (dry, daylight safe operatio n) Spatial Resolution: 320 DP I (12.6 pixels/mm) Throughput: Up to 100 films per hour Time To Operate: 5 minutes (ready to print from “of f”) Grayscale Contrast Resolutio n: 12 bits (4096) Media Inputs: One supply cassette, 8 0-100 sheets Media Outputs: One receive tray, 5 0-sheet capacity Media Sizes: 8” x 1 0”, 14” x 17” (blue and clea r), 11” x 14 ”(blu e) DirectVista ® Film Optional A, A4, 14” x 17” Direct Vista Grayscale Paper Dmax: >3.10 with Direct Vista Film Archival: >20 years with DirectVista Film, under ANSI extended-term storage conditions Media Supply: All media is pre-packaged and factory sealed Interfaces: Standard: 10/ 100/1,000 Base-T Ethernet (RJ- 45), Serial Console Network Protocols: Standard: 24 DICOM connections, FT P, LPR Optional: Windows network printing Image Formats: Standard: DICOM, TIFF, GIF, PCX, BMP, PGM, PNG, PPM, XWD, JPEG, SGI (RGB), Sunrise Express “Swa p” Service Sun Raster, Targa Smart Card from imager being replaced Optional: PostScript™ compatibility contains all of your internal settings such a s Image Qualit y: Manual calibration IP addresses, gamma and contras t . -
Optimizing Images for the Web
9/16/2010 Optimizing Images for the Web Optimize Web Applications Improve Performance & Availability of Critical Web-Based Applications. www.ca.com Download Image Resizer Resize & Convert Bulk Images JPEG TIFF GIF RAW BMP JPG PCX etc. avs4you.com/AVS-Image-Converter Free Veer® Images add-in For Microsoft® Office. To Create A Perfect Presentation. Free Download Veer.com/VeerImagesAddin Links To This Guide: Getting Started | What Makes a Good Site | Plan Your Site | Design and Layout | How to Create Your Web By Alan Flum of Celestial Graphics Inc. Pages | How to Put Your Site on the Net | Optimizing Images for the More Information Web E-Commerce Tutorial HTML Tutorial Do you want to make your site load fast Recommended Reading but still look good? This section will tell you how to create fast loading images for Optimizing Images for the your web page. Web What Software Should I Use? The Most Common Mistake Park Your Domain for Free! Web Hosting Packages Once, I was asked to look at why a very simple web page will one small image and about 400 words of text took over 1 minute to load. The answer was simple and is a mistake I see over and over again. The original image, which was large, was scaled to a small image size in a web site creation program, not an image editing program. DO NOT resize your images in your website design program. The result will be a small image with the same file size . DO resize your image in your image editing program. -
Arxiv:2002.01657V1 [Eess.IV] 5 Feb 2020 Port Lossless Model to Compress Images Lossless
LEARNED LOSSLESS IMAGE COMPRESSION WITH A HYPERPRIOR AND DISCRETIZED GAUSSIAN MIXTURE LIKELIHOODS Zhengxue Cheng, Heming Sun, Masaru Takeuchi, Jiro Katto Department of Computer Science and Communications Engineering, Waseda University, Tokyo, Japan. ABSTRACT effectively in [12, 13, 14]. Some methods decorrelate each Lossless image compression is an important task in the field channel of latent codes and apply deep residual learning to of multimedia communication. Traditional image codecs improve the performance as [15, 16, 17]. However, deep typically support lossless mode, such as WebP, JPEG2000, learning based lossless compression has rarely discussed. FLIF. Recently, deep learning based approaches have started One related work is L3C [18] to propose a hierarchical archi- to show the potential at this point. HyperPrior is an effective tecture with 3 scales to compress images lossless. technique proposed for lossy image compression. This paper In this paper, we propose a learned lossless image com- generalizes the hyperprior from lossy model to lossless com- pression using a hyperprior and discretized Gaussian mixture pression, and proposes a L2-norm term into the loss function likelihoods. Our contributions mainly consist of two aspects. to speed up training procedure. Besides, this paper also in- First, we generalize the hyperprior from lossy model to loss- vestigated different parameterized models for latent codes, less compression model, and propose a loss function with L2- and propose to use Gaussian mixture likelihoods to achieve norm for lossless compression to speed up training. Second, adaptive and flexible context models. Experimental results we investigate four parameterized distributions and propose validate our method can outperform existing deep learning to use Gaussian mixture likelihoods for the context model. -
Image Formats
Image Formats Ioannis Rekleitis Many different file formats • JPEG/JFIF • Exif • JPEG 2000 • BMP • GIF • WebP • PNG • HDR raster formats • TIFF • HEIF • PPM, PGM, PBM, • BAT and PNM • BPG CSCE 590: Introduction to Image Processing https://en.wikipedia.org/wiki/Image_file_formats 2 Many different file formats • JPEG/JFIF (Joint Photographic Experts Group) is a lossy compression method; JPEG- compressed images are usually stored in the JFIF (JPEG File Interchange Format) >ile format. The JPEG/JFIF >ilename extension is JPG or JPEG. Nearly every digital camera can save images in the JPEG/JFIF format, which supports eight-bit grayscale images and 24-bit color images (eight bits each for red, green, and blue). JPEG applies lossy compression to images, which can result in a signi>icant reduction of the >ile size. Applications can determine the degree of compression to apply, and the amount of compression affects the visual quality of the result. When not too great, the compression does not noticeably affect or detract from the image's quality, but JPEG iles suffer generational degradation when repeatedly edited and saved. (JPEG also provides lossless image storage, but the lossless version is not widely supported.) • JPEG 2000 is a compression standard enabling both lossless and lossy storage. The compression methods used are different from the ones in standard JFIF/JPEG; they improve quality and compression ratios, but also require more computational power to process. JPEG 2000 also adds features that are missing in JPEG. It is not nearly as common as JPEG, but it is used currently in professional movie editing and distribution (some digital cinemas, for example, use JPEG 2000 for individual movie frames). -
About Graphics/Digital Images
About Graphics/Digital Images Digital images are found in lots of file formats (types) that are used for various reasons. I liken the file formats to flavors of ice-cream, which you might or might not choose to consume on any given day. One day chocolate is more important than mint; another day you might use vanilla, and on another day you might decide to combine more than one flavor in the same bowl. Likewise, you might choose one type of graphic file for a particular project, but it might be completely inappropriate for another project. What works well for display purposes (keeping it on the computer, or for publication to the internet) might not print well. Something that prints well might be too big a file to post to the internet, or may make your program run too slowly. Also, some authoring programs (like Boardmaker or Classroom Suite) might be written to only understand certain types of image files. Some file types are more common than others, and are more likely to be recognized by the “parent” program (the one you use to display, edit or print your image). Whatever type you pick ultimately depends on how you plan to use the image. The more technical definitions provided below are taken from the glossary found at http://www.photoshopelementsuser.com/glossary.php?letter=B The additional comments I have added, and hopefully let you know why you would care about any of this, anyway. The two biggest types of images I describe here fall loosely into two categories: vector images and bitmap images.