Glitch Art, Compression Artefacts, and Digital Materiality
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A Survey Paper on Different Speech Compression Techniques
Vol-2 Issue-5 2016 IJARIIE-ISSN (O)-2395-4396 A Survey Paper on Different Speech Compression Techniques Kanawade Pramila.R1, Prof. Gundal Shital.S2 1 M.E. Electronics, Department of Electronics Engineering, Amrutvahini College of Engineering, Sangamner, Maharashtra, India. 2 HOD in Electronics Department, Department of Electronics Engineering , Amrutvahini College of Engineering, Sangamner, Maharashtra, India. ABSTRACT This paper describes the different types of speech compression techniques. Speech compression can be divided into two main types such as lossless and lossy compression. This survey paper has been written with the help of different types of Waveform-based speech compression, Parametric-based speech compression, Hybrid based speech compression etc. Compression is nothing but reducing size of data with considering memory size. Speech compression means voiced signal compress for different application such as high quality database of speech signals, multimedia applications, music database and internet applications. Today speech compression is very useful in our life. The main purpose or aim of speech compression is to compress any type of audio that is transfer over the communication channel, because of the limited channel bandwidth and data storage capacity and low bit rate. The use of lossless and lossy techniques for speech compression means that reduced the numbers of bits in the original information. By the use of lossless data compression there is no loss in the original information but while using lossy data compression technique some numbers of bits are loss. Keyword: - Bit rate, Compression, Waveform-based speech compression, Parametric-based speech compression, Hybrid based speech compression. 1. INTRODUCTION -1 Speech compression is use in the encoding system. -
Automatic Detection of Perceived Ringing Regions in Compressed Images
International Journal of Electronics and Communication Engineering. ISSN 0974-2166 Volume 4, Number 5 (2011), pp. 491-516 © International Research Publication House http://www.irphouse.com Automatic Detection of Perceived Ringing Regions in Compressed Images D. Minola Davids Research Scholar, Singhania University, Rajasthan, India Abstract An efficient approach toward a no-reference ringing metric intrinsically exists of two steps: first detecting regions in an image where ringing might occur, and second quantifying the ringing annoyance in these regions. This paper presents a novel approach toward the first step: the automatic detection of regions visually impaired by ringing artifacts in compressed images. It is a no- reference approach, taking into account the specific physical structure of ringing artifacts combined with properties of the human visual system (HVS). To maintain low complexity for real-time applications, the proposed approach adopts a perceptually relevant edge detector to capture regions in the image susceptible to ringing, and a simple yet efficient model of visual masking to determine ringing visibility. Index Terms: Luminance masking, per-ceptual edge, ringing artifact, texture masking. Introduction In current visual communication systems, the most essential task is to fit a large amount of visual information into the narrow bandwidth of transmission channels or into a limited storage space, while maintaining the best possible perceived quality for the viewer. A variety of compression algorithms, for example, such as JPEG[1] and MPEG/H.26xhave been widely adopted in image and video coding trying to achieve high compression efficiency at high quality. These lossy compression techniques, however, inevitably result in various coding artifacts, which by now are known and classified as blockiness, ringing, blur, etc. -
Glitch Studies Manifesto
[email protected]. Amsterdam/Cologne, 2009/2010 http://rosa-menkman.blogspot.com The dominant, continuing search for a noiseless channel has been, and will always be no more than a regrettable, ill-fated dogma. Even though the constant search for complete transparency brings newer, ‘better’ media, every one of these new and improved techniques will always have their own fingerprints of imperfection. While most people experience these fingerprints as negative (and sometimes even as accidents) I emphasize the positive consequences of these imperfections by showing the new opportunities they facilitate. In the beginning there was only noise. Then the artist moved from the grain of celluloid to the magnetic distortion and scanning lines of the cathode ray tube. he wandered the planes of phosphor burn-in, rubbed away dead pixels and now makes performance art based on the cracking of LCD screens. The elitist discourse of the upgrade is a dogma widely pursued by the naive victims of a persistent upgrade culture. The consumer only has to dial #1-800 to stay on top of the technological curve, the waves of both euphoria and disappointment. It has become normal that in the future the consumer will pay less for a device that can do more. The user has to realize that improving is nothing more than a proprietary protocol, a deluded consumer myth about progression towards a holy grail of perfection. Dispute the operating templates of creative practice by fighting genres and expectations! I feel stuck in the membranes of knowledge, governed by social conventions and acceptances. As an artist I strive to reposition these membranes; I do not feel locked into one medium or between contradictions like real vs. -
Lossless Compression of Audio Data
CHAPTER 12 Lossless Compression of Audio Data ROBERT C. MAHER OVERVIEW Lossless data compression of digital audio signals is useful when it is necessary to minimize the storage space or transmission bandwidth of audio data while still maintaining archival quality. Available techniques for lossless audio compression, or lossless audio packing, generally employ an adaptive waveform predictor with a variable-rate entropy coding of the residual, such as Huffman or Golomb-Rice coding. The amount of data compression can vary considerably from one audio waveform to another, but ratios of less than 3 are typical. Several freeware, shareware, and proprietary commercial lossless audio packing programs are available. 12.1 INTRODUCTION The Internet is increasingly being used as a means to deliver audio content to end-users for en tertainment, education, and commerce. It is clearly advantageous to minimize the time required to download an audio data file and the storage capacity required to hold it. Moreover, the expec tations of end-users with regard to signal quality, number of audio channels, meta-data such as song lyrics, and similar additional features provide incentives to compress the audio data. 12.1.1 Background In the past decade there have been significant breakthroughs in audio data compression using lossy perceptual coding [1]. These techniques lower the bit rate required to represent the signal by establishing perceptual error criteria, meaning that a model of human hearing perception is Copyright 2003. Elsevier Science (USA). 255 AU rights reserved. 256 PART III / APPLICATIONS used to guide the elimination of excess bits that can be either reconstructed (redundancy in the signal) orignored (inaudible components in the signal). -
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. -
Understanding Compression of Geospatial Raster Imagery
Understanding Compression of Geospatial Raster Imagery Document Overview This document was created for the North Carolina Geographic Information and Coordinating Council (GICC), http://ncgicc.com, by the GIS Technical Advisory Committee (TAC). Its purpose is to serve as a best practice or guidance document for GIS professionals that are compressing raster images. This document only addresses compressing geospatial raster data and specifically aerial or orthorectified imagery. It does not address compressing LiDAR data. Compression Overview Compression is the process of making data more compact so it occupies less disk storage space. The primary benefit of compressing raster data is reduction in file size. An added benefit is greatly improved performance over a network, because the user is transferring less data from a server to an application; however, compressed data must be decompressed to display in GIS software. The result may be slower raster display in GIS software than data that is not compressed. Compressed data can also increase CPU requirements on the server or desktop. Glossary of Common Terms Raster is a spatial data model made of rows and columns of cells. Each cell contains an attribute value identifying its color and location coordinate. Geospatial raster data like satellite images and aerial photographs are typically larger on average than vector data (predominately points, lines, or polygons). Compression is the process of making a (raster) file smaller while preserving all or most of the data it contains. Imagery compression enables storage of more data (image files) on a disk than if they were uncompressed. Compression ratio is the amount or degree of reduction of an image's file size. -
Mutable Artistic Narratives: Video Art Versus Glitch Art
Mutable Artistic Narratives: Video Art versus Glitch Art Ana Marqués Ibáñez Department of Fine Arts. Didactic of Plastic Expression University of La Laguna Biography Ana holds a PhD in Fine Arts from the Univer- sity of Granada and is a professor in the Fac- ulty of Education at the University of La Laguna, Tenerife. Her PhD thesis focused on the commu- nicative capacity of images in literary classics, including the Divine Comedy, with a compari- son of the illustrations of Dante’s work created by different artists. Ana is a professor in the Early Childhood and Primary Education degree programmes, in which she teaches contemporary art and education. She is also a lecturer and coordinator of the special- isation course in drawing, design and visual arts in the Education Master’s Degree programme. Her current research focuses on promoting play as an element of learning, as well as creating teaching resources related to visual culture for people with disabilities. She has participated in national and international conferences, most re- cently at the Texas Art Education Association conference, where she gave presentations on art installations for children as generators of play and learning, and visual diaries as a form of ex- pression and knowledge. 1172 Synnyt / Origins | 2 / 2019 | Peer-reviewed | Full paper Abstract This project analyses a set of different innovative video formats for their sub- sequent incorporation and application in the fields of art and education. The aim is to conduct a historical review of the evolution of video art, in which images, video and experimental and instrumental sound play an essential role. -
Movement Behind Your Back
Movement Behind Your Back: Cinematic Technology in Light of Simondon’s Philosophy of Technology University of Amsterdam Research Master’s Thesis in Media Studies Department of Media Studies Vladimir Lukin e-mail: [email protected] Supervisor: Dr. Abe Geil Second Reader: Dr. Marie-Aude L. Baronian Third Reader: Dr. Bernhard Rieder “La représentation du mouvement est la raison d’être du cinématographe, sa faculté maîtresse, l’expression fondamentale de son génie. […] l’affinité du cinématographe pour le mouvement va jusqu’à découvrir celui-ci là où notre œil ne sait pas le voir. ” — Jean Epstein, Le Cinéma du diable 2 Abstract Movement is the essence of cinema. But it is not the movement that we see on the screen but movement that happens behind our backs — both literally, in the cinematic apparatus in the movie theater, and metaphorically, for it defies our conceptual grasp. Thus, this thesis addresses the question of technical production of motion — the question which, as Tom Gunning aptly remarks, is “the repressed Freudian subject of film theory”. By drawing upon Gilbert Simondon’s philosophy of technology, this thesis attempts to lay bare the technicity of cinematic technology and also to reveal the reasons why it remains misunderstood and under-theorized in the current debates on the moving image. This thesis contends that cinematic technicity can be defined through the three technical operations, namely, movement data organization, movement analysis, and movement synthesis. As this thesis attempts to demonstrate, the misconception of cinematic technicity occurs on both the technological and conceptual levels. If optical technologies obscure cinematic technicity on the technological level, I claim the concept of the image obscures our conceptual understanding of movement. -
Lossy Audio Compression Identification
2018 26th European Signal Processing Conference (EUSIPCO) Lossy Audio Compression Identification Bongjun Kim Zafar Rafii Northwestern University Gracenote Evanston, USA Emeryville, USA [email protected] zafar.rafi[email protected] Abstract—We propose a system which can estimate from an compression parameters from an audio signal, based on AAC, audio recording that has previously undergone lossy compression was presented in [3]. The first implementation of that work, the parameters used for the encoding, and therefore identify the based on MP3, was then proposed in [4]. The idea was to corresponding lossy coding format. The system analyzes the audio signal and searches for the compression parameters and framing search for the compression parameters and framing conditions conditions which match those used for the encoding. In particular, which match those used for the encoding, by measuring traces we propose a new metric for measuring traces of compression of compression in the audio signal, which typically correspond which is robust to variations in the audio content and a new to time-frequency coefficients quantized to zero. method for combining the estimates from multiple audio blocks The first work to investigate alterations, such as deletion, in- which can refine the results. We evaluated this system with audio excerpts from songs and movies, compressed into various coding sertion, or substitution, in audio signals which have undergone formats, using different bit rates, and captured digitally as well lossy compression, namely MP3, was presented in [5]. The as through analog transfer. Results showed that our system can idea was to measure traces of compression in the signal along identify the correct format in almost all cases, even at high bit time and detect discontinuities in the estimated framing. -
Rosa Menkman: General Glitch Falyn, Olivia, Jane, Mutesi Biography
Rosa Menkman: General Glitch Falyn, Olivia, Jane, Mutesi Biography - A full-time position as a substitute professor at - Born in 1983 New Media at the KHK since 2018 and - Wrote a book, The Glitch Moment(um)- helps expanded on the Resolution Studies curriculum. explain her and her work - She started glitching in 2005 when she was 22 - Won the Collide International Barcelona Award- years old annual international competition that invites - A co-organizer of the GLI.TC/H festival artists of any nationality or age to apply for a - Graduated at the University of Amsterdam in the 3-month residency award by submitting a subject of new media proposal - Fun fact: She is one of the Richest Visual Artist who was born in Kingdom of the Netherlands Art Process ❖ Uses the Quicktime and Cinepak (for moving images and compressions) software for her work ❖ ❖ She embraces the process of not being afraid to break her work as a learning process ❖ ❖ Likes to use opposites to portray; sanity for madness, order for chaos, etc. ❖ ❖ Glitches are a benchmark and threshold to create new problems and continue to find new solutions. ❖ ❖ Unconvers unseen, “too good to be implemented” resolutions to produce a new interpretation through technology ❖ ❖ “Highlights visual artifacts created by accidents in both analogue and digital media” (Loosen Art, 2018) Glitch within Contemporary Art Mistakes and errors are part of our everyday life, by taking all those imperfections you can make a new types of art into that imperfection. As Rosa explained during her Ted-talk speech, glitching was never something she wanted her life, but it later become something she saw it as making art, liking broken items because she can create a new meaning for them. -
CS 1St Year: M&A Types of Compression: the Two Types of Compression Are: Lossy Compression
CS 1st Year: M&A Types of compression: The two types of compression are: Lossy Compression - where data bytes are removed from the file. This results in a smaller file, but also lower quality. It makes use of data redundancies and human perception – for example, removing data that cannot be perceived by humans. So whilst quality might be affected, the substance of the file is still present. Lossy compression would be commonly used over the internet, where large files present a problem. An example of lossy compression is “mp3” compression, which removes wavelength extremes which are out of the hearing range of normal people. MP3 has a compression ratio of 11:1. Another example would be JPEG (Joint Photographics Expert Group), which is used to compress images. JPEG works by grouping pixels of an image which have similar colour or brightness, and changing them all to a uniform, “average” colour, and then replaces the similar pixels with codes. The Lossy compression method eliminates some amount of data that is not noticeable. This technique does not allow a file to restore in its original form but significantly reduces the size. The lossy compression technique is beneficial if the quality of the data is not your priority. It slightly degrades the quality of the file or data but is convenient when one wants to send or store the data. This type of data compression is used for organic data like audio signals and images. Lossy Compression Technique Transform coding: This method transforms the pixels which are correlated in a representation into disassociated pixels. -
Vendela Grundell
FLOW AND FRICTION: ON THE TACTICAL PO T E N T I A L O F I N T ERFAC ING WITH GLITCH ART Vendela Grundell Flow and Friction On the Tactical Potential of Interfacing with Glitch Art Vendela Grundell © Vendela Grundell, Stockholm University 2016 © Cover image: Phillip Stearns’s Year of the Glitch no. 64, 2012 © Case study images: Phillip Stearns, Rosa Menkman, and Evan Meaney. Images reproduced with kind permission of the artists. ISBN 978-91-7649-412-7 Printed in Sweden by Holmbergs, Malmö, 2016 Distributor: Department of Culture and Aesthetics Funded by Konung Gustaf VI Adolfs fond för svensk kultur, and Anders Karitz Stiftelse. Contents Introduction 7 Aims and Questions 9 Material 10 Method 12 Case Study 12 Phenomenology 14 Theory and Previous Research 19 Systems Aesthetics 20 Glitch 22 Interface 28 Photography 30 Outline 34 Building an Unstable Photograph: Phillip Stearns’s Year of the Glitch 35 Screen Image I: Index 35 Screen Image II: Archive 39 Photographic Instance I: Apparatus 47 Photographic Instance II: Text 56 Photographic Instance III: Materialization 64 Interfacing an Unstable Photograph: Rosa Menkman’s Sunshine in My Throat 71 Screen Image I: Index 71 Screen image II: Videoscapes 81 Photographic Instance I: Compress Process 82 Photographic Instance II: Combing 90 Photographic Instance III: Negotiation 98 Sharing an Unstable Photograph: Evan Meaney’s Ceibas Cycle 107 Screen Image I: Ceibas Cycle 107 Screen Image II: A Similar History 114 Photographic Instance I: To Hold a Future Body so Close to One’s Own 122 Photographic Instance