Document and Image Compression
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Although it's true that image compression research is a mature field, continued improvements in computing power and image representation tools keep the field spry. Faster processors enable previously intractable compression algorithms and schemes, and certainly the demand for highly portable high-quality images will not abate. Document and Image Compression highlights the current state of the field along with the most probable and promising future research directions for image coding.
Organized into three broad sections, the book examines the currently available techniques, future directions, and techniques for specific classes of images. It begins with an introduction to multiresolution image representation, advanced coding and modeling techniques, and the basics of perceptual image coding. This leads to discussions of the JPEG 2000 and JPEG-LS standards, lossless coding, and fractal image compression. New directions are highlighted that involve image coding and representation paradigms beyond the wavelet-based framework, the use of redundant dictionaries, the distributed source coding paradigm, and novel data-hiding techniques. The book concludes with techniques developed for classes of images where the general-purpose algorithms fail, such as for binary images and shapes, compound documents, remote sensing images, medical images, and VLSI layout image data.
Contributed by international experts, Document and Image Compression gathers the latest and most important developments in image coding into a single, convenient, and authoritative source.
Organized into three broad sections, the book examines the currently available techniques, future directions, and techniques for specific classes of images. It begins with an introduction to multiresolution image representation, advanced coding and modeling techniques, and the basics of perceptual image coding. This leads to discussions of the JPEG 2000 and JPEG-LS standards, lossless coding, and fractal image compression. New directions are highlighted that involve image coding and representation paradigms beyond the wavelet-based framework, the use of redundant dictionaries, the distributed source coding paradigm, and novel data-hiding techniques. The book concludes with techniques developed for classes of images where the general-purpose algorithms fail, such as for binary images and shapes, compound documents, remote sensing images, medical images, and VLSI layout image data.
Contributed by international experts, Document and Image Compression gathers the latest and most important developments in image coding into a single, convenient, and authoritative source.
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Mauro Barni has carried out his research activities for over 14 years, first at the Department of Electronics and Telecommunication of the University of Florence, then at the Department of Information Engineering of the University of Siena, where he presently works as Associate Professor. During the last decade, his research activity has focused on digital image processing. More recently, he has been studying the application of image processing techniques to copyright protection and authentication of multimedia (digital watermarking), and to the transmission of images and video signals in error-prone, wireless environments. He is the author/co-author of more than 160 papers published in international journals and conference proceedings. He is the co-author of the book Watermarking Systems Engineering: Enabling Digital Assets Security and Other Applications, published by Dekker Inc. in February 2004.
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