Stereoscopic Image Quality Assessment: 60 - Rilegato

Ding, Yong; Sun, Guangming

Rilegato

ISBN 10: 9811577633 ISBN 13: 9789811577635

Casa editrice: Springer-Nature New York Inc, 2020

Riassunto

This book provides a comprehensive review of all aspects relating to visual quality assessment for stereoscopic images, including statistical mathematics, stereo vision and deep learning. It covers the fundamentals of stereoscopic image quality assessment (SIQA), the relevant engineering problems and research significance, and also offers an overview of the significant advances in visual quality assessment for stereoscopic images, discussing and analyzing the current state-of-the-art in SIQA algorithms, the latest challenges and research directions as well as novel models and paradigms. In addition, a large number of vivid figures and formulas help readers gain a deeper understanding of the foundation and new applications of objective stereoscopic image quality assessment technologies.

Reviewing the latest advances, challenges and trends in stereoscopic image quality assessment, this book is a valuable resource for researchers, engineers and graduate students working in related fields, including imaging, displaying and image processing, especially those interested in SIQA research.

Su questo libro

Informazioni sull?autore

Yong Ding received his B.S. and M.S. degrees from the School of Electronic Science & Applied Physics, Hefei University of Technology, P. R. China, in 1997 and 2000, respectively, and his Ph.D. from the College of Electronic Science & Engineering, Nanjing, P. R. China, in 2008. From 2000 to 2006, he was a Senior Engineer at the R & D Center of Hisense, and from 2006 to 2008 was a Senior Project Leader at the Architecture Design Department at Ominivision. He is currently a Professor at the Institute of VLSI Design at Zhejiang University, and is Vice-Director of the Engineering Research Center of Embedded Systems, Ministry of Education of China. He was a Visiting Scholar at the Laboratory of Mathematical Methods of Image Processing at Moscow Lomonosov State University, Russia, in 2011, and at Illinois Institute of Technology, USA, from 2015 to 2016.

His research interests include objective image quality assessment, digital image/video processing and associated SoC architectures. At present, he is in charge of several projects supported by the Chinese government, including the National High Technology Program (863 programs), and a National Science and Technology Major Project, which focus on image quality assessment and video processing.

Prof. Ding has authored more than 70 papers in journals in these fields, and has given several plenary or invited talks at international conferences. He holds more than 30 Chinese patents. He is an editor of the International Journal of Digital Content Technology and its Applications (JDCTA) and an invited reviewer for several leading international publishers.

Guangming Sun is currently a postgraduate at the College of Information Science and Electronics, Zhejiang University, Hangzhou, P. R. China.

Dalla quarta di copertina

This book provides a comprehensive review of all aspects relating to visual quality assessment for stereoscopic images, including statistical mathematics, stereo vision and deep learning. It covers the fundamentals of stereoscopic image quality assessment (SIQA), the relevant engineering problems and research significance, and also offers an overview of the significant advances in visual quality assessment for stereoscopic images, discussing and analyzing the current state-of-the-art in SIQA algorithms, the latest challenges and research directions as well as novel models and paradigms. In addition, a large number of vivid figures and formulas help readers gain a deeper understanding of the foundation and new applications of objective stereoscopic image quality assessment technologies.

Reviewing the latest advances, challenges and trends in stereoscopic image quality assessment, this book is a valuable resource for researchers, engineers and graduate students working in related fields, including imaging, displaying and image processing, especially those interested in SIQA research.

Dettagli dell?edizione

• Editore: Springer-Nature New York Inc
• Data di pubblicazione: 2020
• Lingua: Inglese
• ISBN 10: 9811577633
• ISBN 13: 9789811577635
• Rilegatura: Copertina rigida
• Numero edizione: 1
• Numero di pagine: 180
• Contatto del produttore: {language_tag:it_IT,value:"Springer Nature Customer Service Center GmbH; ProductSafety@springernature.com"}