Design of Video Quality Metrics with Multi-Way Data Analysis A data
This book proposes a data-driven methodology using multi-way data analysis for the design of video-quality metrics. It also enables video- quality metrics to be created using arbitrary features. This data- driven design approach not only requires no detai
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Christian Keimel
Design of Video Quality Metrics with Multi-Way Data Analysis A Data Driven Approach
T-Labs Series in Telecommunication Services Series editors Sebastian Möller, Berlin, Germany Axel Küpper, Berlin, Germany Alexander Raake, Berlin, Germany
More information about this series at http://www.springer.com/series/10013
Christian Keimel
Design of Video Quality Metrics with Multi-Way Data Analysis A Data Driven Approach
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Christian Keimel Munich, Bayern Germany
ISSN 2192-2810 ISSN 2192-2829 (electronic) T-Labs Series in Telecommunication Services ISBN 978-981-10-0268-7 ISBN 978-981-10-0269-4 (eBook) DOI 10.1007/978-981-10-0269-4 Library of Congress Control Number: 2015957792 © Springer Science+Business Media Singapore 2016 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. Printed on acid-free paper This Springer imprint is published by SpringerNature The registered company is Springer Science+Business Media Singapore Pte Ltd.
Preface
Video signal processing and chemistry are at first glance very different domains. Yet in both domains similar problems are encountered when not directly measurable quantities need to be measured. Each domain developed methods to address this issue: in chemistry, chemometrics aims at describing not directly measurable properties in chemical systems, whereas in video signal processing, video quality metrics aims at providing the similarly unmeasurable quality of distorted video signals. Unlike in the design of video quality metrics, a data driven approach to the design of prediction models for quality assessment is well established in chemometrics. In this book, the lessons learned and methods developed from chemometrics are therefore applied to the design of video quality metrics. It provides the reader with both an understanding of the fundamental data driven approach and associated methods from chemometrics, and its extension and application to the design of video quality metrics. The main focus is on how to build prediction
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