Compressive Imaging: Structure, Sampling, Learning
eBook - PDF

Compressive Imaging: Structure, Sampling, Learning

  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

Compressive Imaging: Structure, Sampling, Learning

About this book

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.

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Yes, you can access Compressive Imaging: Structure, Sampling, Learning by Ben Adcock,Anders C. Hansen in PDF and/or ePUB format, as well as other popular books in Computer Science & Computer Science General. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half-title
  3. Title page
  4. Copyright information
  5. Dedication
  6. Contents
  7. Preface
  8. 1 Introduction
  9. Part I The Essentials of Compressive Imaging
  10. Part II Compressed Sensing, Optimization and Wavelets
  11. Part III Compressed Sensing with Local Structure
  12. Part IV Compressed Sensing for Imaging
  13. Part V From Compressed Sensing to Deep Learning
  14. Epilogue
  15. Appendices
  16. Notation
  17. Abbreviations
  18. References
  19. Index