Compressive Imaging: Structure, Sampling, Learning (Hardcover)

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.

General

Imprint:	Cambridge UniversityPress
Country of origin:	United Kingdom
Release date:	September 2021
Authors:	Ben Adcock • Anders C. Hansen
Dimensions:	248 x 174 x 31mm (L x W x T)
Format:	Hardcover
Pages:	614
ISBN-13:	978-1-108-42161-4
Categories:	Books > Computing & IT > General theory of computing > Mathematical theory of computation Books > Computing & IT > Computer programming > General Books > Computing & IT > Applications of computing > Signal processing Books > Science & Mathematics > Mathematics > Calculus & mathematical analysis > Vector & tensor analysis Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning Books > Computing & IT > Applications of computing > Image processing > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Applied optics > General Promotions
LSN:	1-108-42161-X
Barcode:	9781108421614

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