Advances in Visual Data Compression and Communication
Meeting the Requirements of New Applications
Series: Multimedia Computing, Communication and Intelligence;
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Product details:
- Edition number 1
- Publisher Auerbach Publications
- Date of Publication 25 July 2014
- ISBN 9781482234138
- Binding Hardback
- No. of pages513 pages
- Size 234x156 mm
- Weight 894 g
- Language English
- Illustrations 198 Illustrations, black & white; 33 Tables, black & white 0
Categories
Short description:
This book provides a theoretical and technical basis for advanced research on visual data compression and communication. It presents the results of the author’s research on visual data compression and transmission. Studying scalable video coding (SVC), it considers the fundamental problem to be solved in SVC—motion compensation. It explores directional transforms, extends the current coding framework by visual synthesis and reconstruction, and explains how to apply compressive sensing to solve the compression problems in transmission. It also develops the pseudo-analog transmission for image and video.
MoreLong description:
Visual information is one of the richest and most bandwidth-consuming modes of communication. To meet the requirements of emerging applications, powerful data compression and transmission techniques are required to achieve highly efficient communication, even in the presence of growing communication channels that offer increased bandwidth.
Presenting the results of the author’s years of research on visual data compression and transmission, Advances in Visual Data Compression and Communication: Meeting the Requirements of New Applications provides a theoretical and technical basis for advanced research on visual data compression and communication.
The book studies the drifting problem in scalable video coding, analyzes the reasons causing the problem, and proposes various solutions to the problem. It explores the author’s Barbell-based lifting coding scheme that has been adopted as common software by MPEG. It also proposes a unified framework for deriving a directional transform from the nondirectional counterpart. The structure of the framework and the statistic distribution of coefficients are similar to those of the nondirectional transforms, which facilitates subsequent entropy coding.
Exploring the visual correlation that exists in media, the text extends the current coding framework from different aspects, including advanced image synthesis—from description and reconstruction to organizing correlated images as a pseudo sequence. It explains how to apply compressive sensing to solve the data compression problem during transmission and covers novel research on compressive sensor data gathering, random projection codes, and compressive modulation.
For analog and digital transmission technologies, the book develops the pseudo-analog transmission for media and explores cutting-edge research on distributed pseudo-analog transmission, denoising in pseudo-analog transmission, and supporting MIMO. It concludes by considering emerging developments of information theory for future applications.
Table of Contents:
Basis for Compression and Communication. Information Theory. Hybrid Video Coding. Communication. Scalable Video Coding. Progressive Fine Granularity Scalable (PFGS) Coding. Motion Threading for 3D Wavelet Coding. Barbell-Lifting Based 3D Wavelet Coding. Directional Transforms. DirectionalWavelet Transform. Directional DCT Transform. Directional Filtering Transform. VISION-BASED COMPRESSION. Edge-Based Inpainting. Cloud-Based Image Compression. Compression for Cloud Photo Storage. Compressive Communication. Compressive Data Gathering. Compressive Modulation. Joint Source and Channel Coding. DCast: Distributed Video Multicast. Denoising in Communication. MIMO Broadcasting with Receiver Antenna Heterogeneity. Future Work. Computational Information Theory.
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