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Fundamental Data Compression provides all the information students need to be able to use this essential technology in their future careers. A huge, active research field, and a part of many people's everyday lives, compression technology is an essential part of today's Computer Science and Electronic Engineering courses. With the help of this book, students can gain a thorough understanding of the underlying theory and algorithms, as well as specific techniques used in a range of scenarios, including the application of compression techniques to text, still images, video and aud

Data compression (Computer science) --- Algorithms. --- Computer algorithms. --- Algorism --- Compression of data (Computer science) --- Compression of files (Computer science) --- Compression of text (Computer science) --- File compression (Computer science) --- Text compression (Computer science) --- Algorithms --- Algebra --- Arithmetic --- Coding theory --- Database management --- File organization (Computer science) --- Data compression (Telecommunication) --- Foundations --- Computer algorithms --- Données --- Algorithmes --- Compression (Informatique)

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In life, time is money, and on the Internet, the size of data is money. Small programs and small files take less disk space and cost less to send over the Internet. Compression Algorithms for Real Programmers describes the basic algorithms and approaches for compressing information so you can create the smallest files possible. These new algorithms are making it possible for people to take impossibly large audio and video files and compress them enough that they can flow over the Internet.* Examines the classic algorithms like Huffman coding, arithmetic compression, and dictio

Computer algorithms. --- Real-time programming. --- Data compression (Computer science) --- Compression of data (Computer science) --- Compression of files (Computer science) --- Compression of text (Computer science) --- File compression (Computer science) --- Text compression (Computer science) --- Coding theory --- Database management --- File organization (Computer science) --- Data compression (Telecommunication) --- Computer programming --- Real-time data processing --- Algorithms --- Data compression (Computer science).

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Good quality digital images have high storage and bandwidth requirements. In modern times, with increasing user expectation for image quality, efficient compression is necessary to keep memory and transmission time within reasonable limits. Image compression is concerned with minimization of the number of information carrying units used to represent an image. Lossy compression techniques incur some loss of information which is usually imperceptible. In return for accepting this distortion, we obtain much higher compression ratios than is possible with lossless compression. Salient features of this book include: Four new image compression algorithms and implementation of these algorithms Detailed discussion of fuzzy geometry measures and their application in image compression algorithms New domain decomposition based algorithms using image quality measures and study of various quality measures for gray scale image compression Compression algorithms for different parallel architectures and evaluation of time complexity for encoding on all architectures Parallel implementation of image compression algorithms on a cluster in Parallel Virtual Machine (PVM) environment. This book will be of interest to graduate students, researchers and practicing engineers looking for new image compression techniques that provide good perceived quality in digital images with higher compression ratios than is possible with conventional algorithms.

Image compression. --- Image processing -- Digital techniques. --- Image processing. --- Data compression (Computer science) --- Engineering & Applied Sciences --- Applied Physics --- Computer Science --- Compression of data (Computer science) --- Compression of files (Computer science) --- Compression of text (Computer science) --- File compression (Computer science) --- Text compression (Computer science) --- Computer science. --- Computer Science. --- Image Processing and Computer Vision. --- Coding theory --- Database management --- File organization (Computer science) --- Data compression (Telecommunication) --- Computer vision. --- Machine vision --- Vision, Computer --- Artificial intelligence --- Image processing --- Pattern recognition systems --- Optical data processing. --- Optical computing --- Visual data processing --- Bionics --- Electronic data processing --- Integrated optics --- Photonics --- Computers --- Optical equipment

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This book treats the Mathematics of many important areas in digital information processing. It covers, in a unified presentation, five topics: Data Compression, Cryptography, Sampling (Signal Theory), Error Control Codes, Data Reduction. The thematic choices are practice-oriented. So, the important final part of the book deals with the Discrete Cosine Transform and the Discrete Wavelet Transform, acting in image compression. The presentation is dense, the examples and numerous exercises are concrete. The pedagogic architecture follows increasing mathematical complexity. A read-and-learn book on Concrete Mathematics, for teachers, students and practitioners in Electronic Engineering, Computer Science and Mathematics.

Data compression (Computer science) --- Cryptography --- Error-correcting codes (Information theory) --- Signal theory (Telecommunication) --- Algebra --- Coding theory. --- Information theory. --- Mathematics. --- Data processing. --- Data compression (Telecommunication) --- Digital electronics --- Information theory --- Machine theory --- Computer programming --- Communication theory --- Communication --- Cybernetics --- Electric signal theory --- Electric waves --- Signal detection --- Telecommunication --- Codes, Error-correcting (Information theory) --- Error-detecting codes (Information theory) --- Forbidden-combination check (Information theory) --- Self-checking codes (Information theory) --- Artificial intelligence --- Automatic control --- Coding theory --- Compression of data (Computer science) --- Compression of files (Computer science) --- Compression of text (Computer science) --- File compression (Computer science) --- Text compression (Computer science) --- Database management --- File organization (Computer science) --- Cryptanalysis --- Cryptology --- Secret writing --- Steganography --- Signs and symbols --- Symbolism --- Writing --- Ciphers --- Data encryption (Computer science)

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With today's flood of data circulating on storage media and the Internet, compression of digital data remains an immensely important aspect of data transmission and storage. This essential explains, without theoretical superstructure and with elementary mathematical methods, the most important compression methods, such as the entropy encodings of Shannon-Fano and of Huffman, as well as the dictionary encodings of the Lempel-Ziv family. Irrelevance reduction and quantization for optical and acoustic signals, which exploit the inadequacies of the human eye and ear for data compression, are also discussed in detail. The whole is illustrated by means of common practical applications from the everyday environment. The presentation allows for use in, for example, working groups at schools, introductory courses at universities, and is also suitable for interested laypersons. This Springer essential is a translation of the original German 1st edition essentials, Gut gepackt – Kein Bit zu viel by Olaf Manz, published by Springer Fachmedien Wiesbaden GmbH, part of Springer Nature in 2020. The translation was done with the help of artificial intelligence (machine translation by the service DeepL.com). A subsequent human revision was done primarily in terms of content, so that the book will read stylistically differently from a conventional translation. Springer Nature works continuously to further the development of tools for the production of books and on the related technologies to support the authors. The Content · Data transmission and storage · Digitization · Overview of data compression methods · Entropy encodings · Dictionary encodings · Quantization The Author Dr. Olaf Manz worked as a research assistant and Heisenberg professor at the mathematical institutes of the universities of Mainz and Heidelberg. He then worked for many years at Siemens in IT product management and also knows data processing from the practical side. He is the author of the books "Fehlerkorrigierende Codes" and "Verschlüsseln, Signieren, Angreifen" published by Springer.

Compressió de dades (Informàtica) --- Compressió de fitxers (Informàtica) --- Descompressió de dades (Informàtica) --- Gestió de bases de dades --- Teoria de la codificació --- Compressió d'imatges --- Compressió de dades (Telecomunicació) --- Data compression (Computer science) --- Compression of data (Computer science) --- Compression of files (Computer science) --- Compression of text (Computer science) --- File compression (Computer science) --- Text compression (Computer science) --- Coding theory --- Database management --- File organization (Computer science) --- Data compression (Telecommunication) --- Computer science --- Data protection. --- Cryptography. --- Data encryption (Computer science). --- Mathematical Applications in Computer Science. --- Data and Information Security. --- Cryptology. --- Mathematics. --- Data encoding (Computer science) --- Encryption of data (Computer science) --- Computer security --- Cryptography --- Cryptanalysis --- Cryptology --- Secret writing --- Steganography --- Signs and symbols --- Symbolism --- Writing --- Ciphers --- Data encryption (Computer science) --- Data governance --- Data regulation --- Personal data protection --- Protection, Data --- Electronic data processing --- Computer mathematics --- Mathematics