Gene Cheung - Graph Spectral Image Processing

1 Chapter 2Table 2.1. Comparison between different GSP-based approaches to graph learning. Table from (Dong et al. 2019) with permission

2 Chapter 4Table 4.1. DCTs/DSTs corresponding to ¯ with different vertex weights Table 4.2. Comparison of KLT, S-GFT and NS-GFT with RDOT scheme in terms of BD-rate ( % bitrate reduction) with respect to the DCT. Smaller (negative) BD-rates mean better compressionTable 4.3. Comparison of KLT, S-GFT and NS-GFT for coding of different prediction modes in terms of BD-rate with respect to the DCT. Smaller (negative) BD-rates mean better compression Table 4.4. The contribution of GL-GFT and EA-GFT in terms of BD-rate with respect to the DCT. Smaller (negative) BD-rates mean better compression

3 Chapter 6Table 6.1. Property comparison of different graph Laplacians Table 6.2. Comparison with different graph variants in PSNR(dB) at QF = 5

4 Chapter 7Table 7.1. Classification accuracy (%) on the ModelNet40 dataset

5 Chapter 9Table 9.1. Classification error rate (%) for the CIFAR10 dataset for different labeling ratios (%) Table 9.2. Classification error rate (%) for the CIFAR10 dataset using sufficient training data under different label noise levels

6 Chapter 10Table 10.1. Mean F1 score weighted by class frequency on Sydney Urban Objects dataset (De Deuge et al. 2013) Table 10.2. Mean class accuracy (respectively, mean instance accuracy) on ModelNet datasets (Wu et al. 2015) Table 10.3. Part segmentation results on ShapeNet part dataset (Yi et al. 2016). The results show the mean computed for all classes; for more detailed results, we refer the reader to (Wang et al. 2019) Table 10.4. Natural image denoising results. The evaluation metric is PSNR (dB) Table 10.5. Quantitative comparisons Table 10.6. Completion error for synthetic range scans.

1 Cover

2 Table of Contents

3 Title Page SCIENCES Image , Field Director – Laure Blanc-Feraud Compression, Coding and Protection of Images and Videos , Subject Head – Christine Guillemot

4 Copyright First published 2021 in Great Britain and the United States by ISTE Ltd and John Wiley & Sons, Inc. 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 and licenses issued by the CLA. Enquiries concerning reproduction outside these terms should be sent to the publishers at the undermentioned address: ISTE Ltd 27-37 St George’s Road London SW19 4EU UK www.iste.co.uk John Wiley & Sons, Inc. 111 River Street Hoboken, NJ 07030 USA www.wiley.com © ISTE Ltd 2021 The rights of Gene Cheung and Enrico Magli to be identified as the author of this work have been asserted by them in accordance with the Copyright, Designs and Patents Act 1988. Library of Congress Control Number: 2021932054 British Library Cataloguing-in-Publication Data A CIP record for this book is available from the British Library ISBN 978-1-78945-028-6 ERC code: PE7 Systems and Communication Engineering PE7_7 Signal processing

5 Introduction to Graph Spectral Image Processing

6 Begin Reading

7 List of Authors

8 Index

9 End User License Agreement

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SCIENCES

Image , Field Director – Laure Blanc-Feraud

Compression, Coding and Protection of Images and Videos , Subject Head – Christine Guillemot