Lossy Image Compression Domain Decomposition-Based Algorithms
Good quality digital images have high storage and bandwidth requirements. In modern times, with increasing user expectation for image quality, efficient compression is necessary to keep memory and transmission time within reasonable limits.Image compressi
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K. K. Shukla M. V. Prasad •
Lossy Image Compression Domain Decomposition-Based Algorithms
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Prof. K. K. Shukla Department of Computer Engineering Indian Institute of Technology Banaras Hindu University Varanasi 221005 India e-mail: [email protected]
ISSN 2191-5768 ISBN 978-1-4471-2217-3 DOI 10.1007/978-1-4471-2218-0
Asst. Prof. M. V. Prasad Institute for Development and Research in Banking Technology Castle Hills, Road No. 1 Hyderabad 500057 India e-mail: [email protected]
e-ISSN 2191-5776 e-ISBN 978-1-4471-2218-0
Springer London Dordrecht Heidelberg New York British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library Ó K. K. Shukla 2011 Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms of licenses issued by the Copyright Licensing Agency. Enquiries concerning reproduction outside those terms should be sent to the publishers. The use of registered names, trademarks, etc., in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant laws and regulations and therefore free for general use. The publisher makes no representation, express or implied, with regard to the accuracy of the information contained in this book and cannot accept any legal responsibility or liability for any errors or omissions that may be made. Cover design: eStudio Calamar, Berlin/Figueres Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
Preface
Image data compression is concerned with minimization of the number of information carrying units used to represent an image. Image compression schemes can be divided into two broad classes: lossless compression schemes and lossy compression schemes. Lossless compression techniques, as their name implies aim at exact reconstruction and involve no loss of information. Lossy compression techniques accept some loss of information, therefore images compressed using a lossy technique cannot be reconstructed exactly. The distortion in the image caused by lossy compression may be imperceptible to humans and we obtain much higher compression ratios than is possible with lossless compression. Lossy compression scheme can be further divided into three major categories: 1. Transform coding, 2. Fractal image compression, and 3. Domain Decomposition. Joint Photographic Expert Group (JPEG), JPEG2000, Binary Tree Triangular Coding (BTTC) etc. are the examples of lossy image compression methods. This book descri
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