Buch, Englisch, 456 Seiten, Format (B × H): 178 mm x 254 mm, Gewicht: 998 g
Buch, Englisch, 456 Seiten, Format (B × H): 178 mm x 254 mm, Gewicht: 998 g
Reihe: Signal Processing and Communications
ISBN: 978-0-8493-3556-3
Verlag: CRC Press
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.
Zielgruppe
Engineers, students, and researchers in signal and image processing, computer science, multimedia, telecommunications, optical engineering, computer vision, and electrical and electronics engineering.
Autoren/Hrsg.
Weitere Infos & Material
STATE OF THE ARTMultiresolution Analysis for Image Compression; Luciano Alparone, Fabrizio Argenti, and Tiziano BianchiIntroductionWavelet Analysis and Filter BanksEnhanced Laplacian PyramidCoding SchemesConclusionsReferencesAdvanced Modeling and Coding Techniques for Image Compression; David TaubmanIntroductionIntroduction to Entropy and CodingArithmetic Coding and Context ModelingInformation Sequencing and EmbeddingOverview of EBCOTReflectionsReferencesPerceptual Aspects of Image Coding; Alessandro Neri, Marco Carli, and Sanjit K. MitraIntroductionThe Human Vision SystemPhysiological ModelsPerceptual Distortion MetricsEvaluation of the JND ThresholdEffects of Perception in DCT DomainPerception Metrics in the Wavelet DomainConclusionsReferencesThe JPEG Family of Coding Standards; Enrico MagliIntroductionA Brief History of the JPEG Family of StandardsThe JPEG StandardThe JPEG-LS StandardThe JPEG 2000 StandardAdvanced Research Related to Image-Coding StandardsAvailable SoftwareReferencesLossless Image Coding; Søren Forchhammer and Nasir MemonIntroductionGeneral PrinciplesLossless Image Coding MethodsOptimizations of Lossless Image CodingApplication DomainsReferencesFractal Image Compression; Raouf Hamzaoui and Dietmar SaupeIntroductionThe Fractal Image ModelImage PartitionsEncoder Complexity ReductionDecoder Complexity ReductionAttractor CodingRate-Distortion CodingExtensionsState of the ArtConclusionAcknowledgementsReferencesNEW DIRECTIONSBeyond Wavelets: New Image Representation Paradigms; Hartmut Führ, Laurent Demaret, and Felix FriedrichIntroductionThe Problem and Some Proposed SolutionsDigital WedgeletsDigital Curvelets: ContourletsApplication to Image CompressionTentative Conclusions and Suggestions for Further ReadingAcknowledgementsReferencesImage Coding using Redundant Dictionaries; Pierre Vandergheynst and Pascal FrossardIntroductionRedundant ExpansionsDiscussions and ConclusionsAcknowledgementsReferencesDistributed Compression of Field Snapshots in Sensor Networks; Sergio D. ServettoIntroductionDistributed Compression of Sensor MeasurementsTransforms for Distributed Decorrelation of Bandlimited ImagesPhysically Constrained Nonbandlimited ImagesLiterature ReviewConclusionsReferencesData Hiding for Image and Video Coding; Patrizio Campisi and Alessandro PivaIntroductionData Hiding for Image and Video CompressionData Hiding for Error ConcealmentFinal CommentsFurther ReadingsAcknowledgementsReferencesDOMAIN-SPECIFIC CODINGBinary Image Compression; Charles BonceletIntroductionBinary ImagesGroup 3 and 4 Facsimile AlgorithmsJBIG and JBIG2Context Weighting Applied to Binary CompressionConclusionsReferencesTwo-Dimensional Shape Coding; Joern Ostermann and Anthony VetroIntroductionMPEG-4 Shape Coding ToolsCodec OptimizationApplicationsConcluding RemarksReferencesCompressing Compound Documents; Ricardo L. de QueirozIntroductionRaster Imaging ModelsMRC for CompressionA Simple MRC: JPEG+MMR+JPEGMRC within JPEG 2000ConclusionsReferencesTrends in Model-Based Coding of Multidimensional Medical Data; Gloria MenegazIntroductionRequirementsState of the Art3-D/2-D ROI-Based MLZC: A 3-D Encoding/2-D Decoding Object-Bases ArchitectureObject-Based ProcessingMultidimensional Layered Zero CodingResults and DiscussionConclusionsReferencesRemote-Sensing Image Coding; Bruno Aiazzi, Stefano Baronti, and Cinzia LastriIntroductionQuality Issues in Remote-Sensing Data CompressionDistortion MeasuresAdvanced Compression Algorithms for Remote-Sensing ImagesNear-Lossless Compression through 3D Causal DPCMNear-Lossless Image Compression through Noncausal DPCMExperimental ResultsConclusionsReferencesLossless Compression of VLSI Layout Image Data; Vito Dai and Avideh ZakhorIntroductionOverview of C4Context-Based Prediction ModelCopy Regions and SegmentationHierarchical Combinatorial CodingExtension to Gray PixelsCompression ResultsSummaryAcknowledgementReferencesIndex
