Compressive Imaging: Structure, Sampling, Learning Adcock Ben

Accurate, robust and fast image reconstruction is a critical task in many scientific, industrial and medical applications. It has fundamentally changed the way modern image reconstruction is performed. Over the last decade, image reconstruction has been revolutionized by the rise of compressive imaging.

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. 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. 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