Description
Accurate, robust and fast image reconstruction is a critical task in many scientific, industrial and medical applications. Over the last decade, image reconstruction has been revolutionized by the rise of compressive imaging. It has fundamentally changed the way modern image reconstruction is performed. This in-depth treatment of the subject commences with a practical introduction to compressive imaging, supplemented with examples and downloadable code, intended for readers without extensive background in the subject. Next, it introduces core topics in compressive imaging - including compressed sensing, wavelets and optimization - in a concise yet rigorous way, before providing a detailed treatment of the mathematics of compressive imaging. The final part is devoted to recent trends in compressive imaging: deep learning and neural networks. With an eye to the next decade of imaging research, and using both empirical and mathematical insights, it examines the potential benefits and the pitfalls of these latest approaches.
This is a practical, rigorous guide to the compressive imaging revolution that has fundamentally changed modern image reconstruction.
About the Author
Ben Adcock is Associate Professor of Mathematics at Simon Fraser University. He received the CAIMS/PIMS Early Career Award (2017), an Alfred P. Sloan Research Fellowship (2015) and a Leslie Fox Prize in Numerical Analysis (2011). He has published fifteen conference proceedings, two book chapters and over fifty peer-reviewed journal articles. His work has been published in outlets such as SIAM Review and Proceedings of the National Academy of Sciences, and featured on the cover of SIAM News. Anders C. Hansen is Reader in Mathematics at University of Cambridge and Professor of Mathematics at the University of Oslo. He received the Leverhulme Prize in Mathematics and Statistics (2017), the 2018 IMA Prize in Mathematics and Applications and the Whitehead Prize (2019). He has had papers published in outlets such as the Journal of the American Mathematical Society and Proceedings of the National Academy of Sciences, and featured on the cover of Physical Review Letters and SIAM News.
Book Information
ISBN 9781108421614
Author Ben Adcock
Format Hardback
Page Count 614
Imprint Cambridge University Press
Publisher Cambridge University Press
Weight(grams) 1340g
Dimensions(mm) 248mm * 174mm * 31mm
This is a practical, rigorous guide to the compressive imaging revolution that has fundamentally changed modern image reconstruction.
About the Author
Ben Adcock is Associate Professor of Mathematics at Simon Fraser University. He received the CAIMS/PIMS Early Career Award (2017), an Alfred P. Sloan Research Fellowship (2015) and a Leslie Fox Prize in Numerical Analysis (2011). He has published fifteen conference proceedings, two book chapters and over fifty peer-reviewed journal articles. His work has been published in outlets such as SIAM Review and Proceedings of the National Academy of Sciences, and featured on the cover of SIAM News. Anders C. Hansen is Reader in Mathematics at University of Cambridge and Professor of Mathematics at the University of Oslo. He received the Leverhulme Prize in Mathematics and Statistics (2017), the 2018 IMA Prize in Mathematics and Applications and the Whitehead Prize (2019). He has had papers published in outlets such as the Journal of the American Mathematical Society and Proceedings of the National Academy of Sciences, and featured on the cover of Physical Review Letters and SIAM News.
Book Information
ISBN 9781108421614
Author Ben Adcock
Format Hardback
Page Count 614
Imprint Cambridge University Press
Publisher Cambridge University Press
Weight(grams) 1340g
Dimensions(mm) 248mm * 174mm * 31mm
