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This book presents exciting recent research on the compression of images and text. Part 1 presents the (lossy) image compression techniques of vector quantization, iterated transforms (fractal compression), and techniques that employ optical hardware. Part 2 presents the (lossless) text compression techniques of arithmetic coding, context modeling, and dictionary methods (LZ methods); this part of the book also addresses practical massively parallel architectures for text compression. Part 3 presents theoretical work in coding theory that has applications to both text and image compression. The book ends with an extensive bibliography of data compression papers and books which can serve as a valuable aid to researchers in the field. Points of Interest: Data compression is becoming a key factor in the digital storage of text, speech graphics, images, and video, digital communications, data bases, and supercomputing. The book addresses `hot' data compression topics such as vector quantization, fractal compression, optical data compression hardware, massively parallel hardware, LZ methods, arithmetic coding. Contributors are all accomplished researchers. Extensive bibliography to aid researchers in the field.
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First Sentence:
Image compression maps an original image raster into a bit stream suitable for communication over or storage in a digital medium so that the number of bits required to represent the coded image is smaller than that required for the original image. Read the first page Key Phrases - Capitalized Phrases (CAPs): (learn more)
D-ary Huffman, Output Next, Data Compression Conference, New York, San Diego, San Francisco, Dynamic Dictionary Method, Academic Press, Computer Science Press, Computer Society Press, State Prob, Combinatorial Algorithms, Englewood Cliffs, Stanford University, Variable Rate Coding New!
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Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Image compression maps an original image raster into a bit stream suitable for communication over or storage in a digital medium so that the number of bits required to represent the coded image is smaller than that required for the original image. Read the first page Key Phrases - Capitalized Phrases (CAPs): (learn more)
D-ary Huffman, Output Next, Data Compression Conference, New York, San Diego, San Francisco, Dynamic Dictionary Method, Academic Press, Computer Science Press, Computer Society Press, State Prob, Combinatorial Algorithms, Englewood Cliffs, Stanford University, Variable Rate Coding New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
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17
books
cite this book:
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- Digital Image Compression: Algorithms and Standards (The Springer International Series in Engineering and Computer Science) by Weidong Kou in Front Matter, and Back Matter
- The Image Processing Handbook, Fourth Edition by John C. Russ in Back Matter (1), and Back Matter (2)
- An Introduction to Data Structures and Algorithms (Progress in Theoretical Computer Science) by J.A. Storer in Back Matter (1), and Back Matter (2)
- Image Analysis and Processing: 8th International Conference, ICIAP '95, San Remo, Italy, September 13 - 15, 1995. Proceedings (Lecture Notes in Computer Science) by Carlo Braccini on page 642
- Managing Gigabytes: Compressing and Indexing Documents and Images, Second Edition (The Morgan Kaufmann Series in Multimedia Information and Systems) by Ian H. Witten in Back Matter
See all 17 books citing this book
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