Video Data Compression for Multimedia Computing: Statistically Based and Biologically Inspired Techniques / Edition 1

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Video Data Compression for Multimedia Computing serves as an excellent reference resource for researchers, engineers and practitioners working on video data compression for multimedia computing. By using mathematical tools such as shastic processes analysis and multiresolution representations, and by taking inspirations from perhaps the most sophisticated vision system, the human vision system, the chapters in this book face head-on many of the challenges in this fast moving field.
In addition to serving as an invaluable reference book, Video Data Compression for Multimedia Computing may be used as a text for advanced courses covering the subject.

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Editorial Reviews

A reference for researchers, engineers, and advanced students, stressing mathematical tools such as stochastic process analysis and multiresolution representations. Contains chapters on wavelet-based video compression, spatial temporal prediction for video data compression, Gibbs-Markov models for motion computation, HDTV, visual motion processing and detection, object tracking using hierarchical 2- D mesh modeling for content based video compression, very low bit rate coding, and motion vector prediction based on frame differences. Annotation c. by Book News, Inc., Portland, Or.
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Product Details

Table of Contents

Preface. 1. Wavelet-Based Video Compression; Ya-Qin Zhang, S. Zafar. 2. Video Compression Using Adaptive Wavelet Packets and DPCM; Wei-Lien Hsu, H. Derin. 3. Spatial Temporal Prediction for Video Data Compression; H.H. Li, Shan Sun. 4. On Gibbs-Markov Models for Motion Computation; J. Konrad, C. Stiller. 5. The HDTV Grand Alliance System; E. Petajan. 6. Visual Motion Processing and Detection - from Biology to Modeling; R. Wang. 7. Object Tracking Using Hierarchical 2-D Mesh Modeling for Content Based Video Compression; C. Toklu, et al. 8. Separation of Moving Regions from Background in an Image Sequence Acquired with a Mobile Camera; J.M. Odobez, P. Bouthemy. 9. Very Low Bit Rate Video Coding Based on Statistical Spatio-Temporal Prediction of Motion, Segmentation and Intensity Fields; T. Özçelik, A.K. Katsaggelos. 10. Gibbs Model Based 3D Motion and Structure Estimation for Object-Based Video Coding Application; A.A. Alatan, L. Onural. 11. Motion Vector Prediction Based on Frame Differences; H.H. Li, et al. Index.

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