Novel Image Compression Methods Based on Vector Quantization

M. Mary Shanthi Rani

ISBN 10: 3659662739 / ISBN 13: 9783659662737

Published by LAP LAMBERT Academic Publishing, 2014

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - The rapid growth and development of electronic imaging in the recent years has led to large scale digital media archives. These are increasingly becoming popular as more and more digital media contents are created and deployed online every day. A critical issue in designing such archives is effective storage of the data. Uncompressed data requires more storage and huge bandwidth for transmission. Though the cost of storage is rapidly dropping, compression still remains as a challenging issue due to the growing number of multimedia based online applications. This necessitates the design of highly efficient image compression systems which promise good image quality and compression ratios with low computational complexity. This book is an outcome of the research in vector quantization based methods for compressing still images. It discusses novel image compression methods with performance analysis using standard compression metrics and their vital role in real-time applications. The proposed methods can be used in applications like Medical Image Processing, Mobile Applications, Biometrics, Remote Sensing and other online web applications.

Seller Inventory # 9783659662737

Bibliographic Details

• Title: Novel Image Compression Methods Based on Vector Quantization
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2014
• Language: English
• ISBN 10: 3659662739
• ISBN 13: 9783659662737
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 12D millimeters 220 millimeters width by 150 millimeters height by 12 millimeters depth
• Weight: 298 grams

About this title

Synopsis

The rapid growth and development of electronic imaging in the recent years has led to large scale digital media archives. These are increasingly becoming popular as more and more digital media contents are created and deployed online every day. A critical issue in designing such archives is effective storage of the data. Uncompressed data requires more storage and huge bandwidth for transmission. Though the cost of storage is rapidly dropping, compression still remains as a challenging issue due to the growing number of multimedia based online applications. This necessitates the design of highly efficient image compression systems which promise good image quality and compression ratios with low computational complexity. This book is an outcome of the research in vector quantization based methods for compressing still images. It discusses novel image compression methods with performance analysis using standard compression metrics and their vital role in real-time applications. The proposed methods can be used in applications like Medical Image Processing, Mobile Applications, Biometrics, Remote Sensing and other online web applications.

About the Author

Ph.D in Computer Science. Has great passion for teaching and research with 10 years of teaching experience in Gandhigram Rural University.Her research areas of interest are Image Compression, Information Security, Ontology, Biometrics and Computational Biology.