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Computational Optical Phase Imaging de Cheng Liu

Computational Optical Phase Imaging: Progress in Optical Science and Photonics, cartea 21

Autor Cheng Liu, Shouyu Wang, Suhas P. Veetil
en Limba Engleză Paperback – 13 apr 2023
In this book, computational optical phase imaging techniques are presented along with Matlab codes that allow the reader to run their own simulations and gain a thorough understanding of the current state-of-the-art.  The book focuses on modern applications of computational optical phase imaging in engineering measurements and biomedical imaging. Additionally, it discusses the future of computational optical phase imaging, especially in terms of system miniaturization and deep learning-based phase retrieval.
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Specificații

ISBN-13: 9789811916434
ISBN-10: 9811916438
Pagini: 312
Ilustrații: X, 301 p. 175 illus., 94 illus. in color.
Dimensiuni: 155 x 235 x 17 mm
Greutate: 0.44 kg
Ediția:1st ed. 2022
Editura: Springer
Colecția Progress in Optical Science and Photonics
Seria Progress in Optical Science and Photonics

Locul publicării:Singapore, Singapore

Cuprins

Introduction to Computational Phase Imaging.- Qualitative Phase Imaging.- Interference Based Quantitative Optical Phase Imaging.- Non-interferometric Quantitative Optical Phase Imaging.- Typical Applications of Computational Phase Imaging.- Recent Trends in Computational Optical Phase Imaging.

Notă biografică

Dr. Xiaowei Li is a Professor and Deputy (Executive) Director at State Key Laboratory of Computer Architecture, Institute of Computing Technology (ICT), Chinese Academy of Sciences (CAS). He received his B.Eng. degree and M.Eng. degree from Hefei University of Technology in 1985 and 1988, and his Ph.D. from ICT, CAS in 1991. He joined Peking University as a post-doc in 1991. From 1993 to 2000, he was an associate professor with the Department of Computer Science at Peking University. From 1997 to 1999, he was a Visiting Research Fellow at The University of Hong Kong and at Nara Institute of Science and Technology, Japan. His research interests include VLSI testing, fault-tolerant computing, multi-core processor design & verification, and hardware security. He has led more than 20 national research projects and helped to develop many systems and software tools in these areas. He holds more than 90 patents and more than 50 software copyrights. He has co-published over 400 peer-reviewed journal and conference papers. He has received many honors and awards, including China National Technology Innovation Award (2012), and China National Science and Technology Progress Award (2015). Dr. Li served on a number of program committees of IEEE/ACM-sponsored conferences and symposia including DAC, ICCAD and DATE, and is currently Vice-Chair of TTTC of the IEEE Computer Society. He also serves as Associate Editors of IEEE TCAD, IEEE TCAS II, and ACM TODAES.
Dr. Guihai Yan is a professor at the State Key Laboratory of Processors (SKLP), Institute of Computing Technology (ICT), Chinese Academy of Sciences (CAS). He received his B.Eng. degree from Peking University in 2005 and his Ph.D. from ICT, CAS in 2011, respectively. His primary research interest is in computer architecture with an emphasis on domain-specific architectures for machine learning and financial computing. He has published more than 40 peer-reviewed papers in leading conference proceedings andjournals including ISCA, HPCA, TC and TVLSI. His research work on fault-tolerant VLSI design has been deployed in countless projects, including 973 high-throughput computing systems and self-repair computer systems.
Dr. Cheng Liu is an associate professor at the State Key Laboratory of Processors (SKLP), Institute of Computing Technology (ICT), Chinese Academy of Sciences (CAS). He received his B.Eng. degree and M.Eng. degree from Harbin Institute of Technology in 2007 and 2009, and his Ph.D. from The University of Hong Kong in 2016. He also worked as a research fellow at National University of Singapore from 2016 to 2018. His research interests include fault-tolerant computing, reconfigurable computing, and customized computing particularly for deep learning and large graph processing. He has published more than 50 peer-reviewed papers in leading conference proceedings and journals for computer architecture and EDA.

Textul de pe ultima copertă

In this book, computational optical phase imaging techniques are presented along with Matlab codes that allow the reader to run their own simulations and gain a thorough understanding of the current state-of-the-art.  The book focuses on modern applications of computational optical phase imaging in engineering measurements and biomedical imaging. Additionally, it discusses the future of computational optical phase imaging, especially in terms of system miniaturization and deep learning-based phase retrieval.

Caracteristici

Provides an overview of recent advances in computational optical phase imaging techniques Includes several MATLAB® simulations along with codes Covers modern applications of computational optical phase imaging in engineering measurements and biomedical imaging Highlights the future of computational optical phase imaging, with emphasis on system miniaturization and deep learning-based phase retrieval