Adrian Stern

"This is the book on how to bypass the sampling constraints of modern imaging systems. From a mathematical point of view, it deals with the problem of extracting information from an underdetermined system of equations. It is wide in its scope, covering applications ranging from holography and microscopy, to hyperspectral or polarization imaging. Readers can easily find out what can be done with this kind of imaging…." –Optics & Photonics News (May 2017)"The material contained in the book’s 300 pages substantiate the assertion that the reader ‘will gain a complete introduction to theory, experiment and practical use for reducing hardware, shortening image scanning time and improving image resolution’…. One is confident that this book will contribute to the growth of activity in compressive imaging and is thus appropriate to repeat the appreciation of the efforts of both the editor and the co-authors in assembling this volume." -Contemporary Physics (Nov 2017), review by K. Alan Shore

• I. The theory of compressive sensing and its applications in optics. Introduction to compressive sensing theory. Compressive sensing theory for optical systems described by a continuous model. Multi-channel data acquisition optics design for compressive sensing. Special challenges in application of CS for optical imaging and sensing II. Compressive imaging systems. Optical architectures for compressive imaging. Terahertz imaging with compressed sensing. Infrared imaging with compressed sensing. Motion compressive sensing. III. Compressive holography and compressive 3D imaging. Compressive holography. Performance analysis of Compressive Holography. Incoherent Compressive Holography. Compressive Integral Imaging. Compressive light-field sensing. IV. Spectral, hyperspectral imaging, and polarimetric compressive sensing systems. Compressive coded aperture spectral imaging. Compressive spectral and hyperspectral sensing with layered devices. Compressive polarimetric sensing. V. Seeing fine details with compressive sensing: microscopy and super-resolution. Super-resolution of sparse images using coherent and incoherent light. Compressive fluorescents microscopy. STORM using compressed sensing. CS methods for lens-free, on-chip microscopy. VI. Phase sensing, phase retrieval and phase tomography. Phase space tomography . Phase retrieval of sparse images.

Adrian Stern

"This is the book on how to bypass the sampling constraints of modern imaging systems. From a mathematical point of view, it deals with the problem of extracting information from an underdetermined system of equations. It is wide in its scope, covering applications ranging from holography and microscopy, to hyperspectral or polarization imaging. Readers can easily find out what can be done with this kind of imaging…." –Optics & Photonics News (May 2017)"The material contained in the book’s 300 pages substantiate the assertion that the reader ‘will gain a complete introduction to theory, experiment and practical use for reducing hardware, shortening image scanning time and improving image resolution’…. One is confident that this book will contribute to the growth of activity in compressive imaging and is thus appropriate to repeat the appreciation of the efforts of both the editor and the co-authors in assembling this volume." -Contemporary Physics (Nov 2017), review by K. Alan Shore

• I. The theory of compressive sensing and its applications in optics. Introduction to compressive sensing theory. Compressive sensing theory for optical systems described by a continuous model. Multi-channel data acquisition optics design for compressive sensing. Special challenges in application of CS for optical imaging and sensing II. Compressive imaging systems. Optical architectures for compressive imaging. Terahertz imaging with compressed sensing. Infrared imaging with compressed sensing. Motion compressive sensing. III. Compressive holography and compressive 3D imaging. Compressive holography. Performance analysis of Compressive Holography. Incoherent Compressive Holography. Compressive Integral Imaging. Compressive light-field sensing. IV. Spectral, hyperspectral imaging, and polarimetric compressive sensing systems. Compressive coded aperture spectral imaging. Compressive spectral and hyperspectral sensing with layered devices. Compressive polarimetric sensing. V. Seeing fine details with compressive sensing: microscopy and super-resolution. Super-resolution of sparse images using coherent and incoherent light. Compressive fluorescents microscopy. STORM using compressed sensing. CS methods for lens-free, on-chip microscopy. VI. Phase sensing, phase retrieval and phase tomography. Phase space tomography . Phase retrieval of sparse images.

Adrian Stern

"This is the book on how to bypass the sampling constraints of modern imaging systems. From a mathematical point of view, it deals with the problem of extracting information from an underdetermined system of equations. It is wide in its scope, covering applications ranging from holography and microscopy, to hyperspectral or polarization imaging. Readers can easily find out what can be done with this kind of imaging…." –Optics & Photonics News (May 2017)"The material contained in the book’s 300 pages substantiate the assertion that the reader ‘will gain a complete introduction to theory, experiment and practical use for reducing hardware, shortening image scanning time and improving image resolution’…. One is confident that this book will contribute to the growth of activity in compressive imaging and is thus appropriate to repeat the appreciation of the efforts of both the editor and the co-authors in assembling this volume." -Contemporary Physics (Nov 2017), review by K. Alan Shore

• I. The theory of compressive sensing and its applications in optics. Introduction to compressive sensing theory. Compressive sensing theory for optical systems described by a continuous model. Multi-channel data acquisition optics design for compressive sensing. Special challenges in application of CS for optical imaging and sensing II. Compressive imaging systems. Optical architectures for compressive imaging. Terahertz imaging with compressed sensing. Infrared imaging with compressed sensing. Motion compressive sensing. III. Compressive holography and compressive 3D imaging. Compressive holography. Performance analysis of Compressive Holography. Incoherent Compressive Holography. Compressive Integral Imaging. Compressive light-field sensing. IV. Spectral, hyperspectral imaging, and polarimetric compressive sensing systems. Compressive coded aperture spectral imaging. Compressive spectral and hyperspectral sensing with layered devices. Compressive polarimetric sensing. V. Seeing fine details with compressive sensing: microscopy and super-resolution. Super-resolution of sparse images using coherent and incoherent light. Compressive fluorescents microscopy. STORM using compressed sensing. CS methods for lens-free, on-chip microscopy. VI. Phase sensing, phase retrieval and phase tomography. Phase space tomography . Phase retrieval of sparse images.