• Presents an overview of the major compression and coding paradigms along with the most likely future trends
• Supplies a convenient point of access to recent developments without having to wade through the literature
• Describes applications of image coding to specific classes of image data including remotely sensed and medical images
• Includes a stable of leading experts who share their knowledge and insights based on original work in the field

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.