Image Quality Assessment of Computer-generated Images Based on Machi
Image Quality Assessment is well-known for measuring the perceived image degradation of natural scene images but is still an emerging topic for computer-generated images. This book addresses this problem and presents recent advances based on soft computin
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André Bigand · Julien Dehos Christophe Renaud Joseph Constantin
Image Quality Assessment of Computergenerated Images Based on Machine Learning and Soft Computing 123
SpringerBriefs in Computer Science Series editors Stan Zdonik, Brown University, Providence, Rhode Island, USA Shashi Shekhar, University of Minnesota, Minneapolis, Minnesota, USA Xindong Wu, University of Vermont, Burlington, Vermont, USA Lakhmi C. Jain, University of South Australia, Adelaide, South Australia, Australia David Padua, University of Illinois Urbana-Champaign, Urbana, Illinois, USA Xuemin Sherman Shen, University of Waterloo, Waterloo, Ontario, Canada Borko Furht, Florida Atlantic University, Boca Raton, Florida, USA V. S. Subrahmanian, University of Maryland, College Park, Maryland, USA Martial Hebert, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA Katsushi Ikeuchi, University of Tokyo, Tokyo, Japan Bruno Siciliano, Università di Napoli Federico II, Napoli, Italy Sushil Jajodia, George Mason University, Fairfax, Virginia, USA Newton Lee, Newton Lee Laboratories, LLC, Burbank, California, USA
More information about this series at http://www.springer.com/series/10028
André Bigand Julien Dehos Christophe Renaud Joseph Constantin •
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Image Quality Assessment of Computer-generated Images Based on Machine Learning and Soft Computing
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André Bigand LISIC Université du Littoral Côte d’Opale Calais Cedex France Julien Dehos Université du Littoral Côte d’Opale Dunkirk France
Christophe Renaud Université du Littoral Côte d’Opale Dunkirk France Joseph Constantin Faculty of Sciences II Lebanese University Beirut Lebanon
ISSN 2191-5768 ISSN 2191-5776 (electronic) SpringerBriefs in Computer Science ISBN 978-3-319-73542-9 ISBN 978-3-319-73543-6 (eBook) https://doi.org/10.1007/978-3-319-73543-6 Library of Congress Control Number: 2018932548 © The Author(s) 2018 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published
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