This book explores the ways to improve the classical resolution limits of an imaging system, and provides novel approaches for achieving better results than would otherwise be possible with current imaging technology. The book begins by presenting the theoretical foundations, background information, and terminology of super resolution, and then discusses methods and systems used to achieve the super resolution effect. Various approaches to dealing with and exceeding the limitations of the lens aperture, the pixel size of the camera, and the noise generated at the detector are presented and analyzed. The last chapter illustrates several industry-related examples and potential applications to real industrial eletro-optical systems. This book is intended for graduate students or researchers in academia or industry, and anyone else looking to improve the performance of their electro-optical system design.

This book explores the ways to improve the classical resolution limitsof an imaging system. The book begins by presenting the theoreticalfoundations, background information, and terminology of superresolution, and then discusses methods and systems used to acheive thesuper resolution effect.

1 Fourier Transform and Fourier Optics.- 1.1 Fourier Transform and Fourier Optics.- 2 Degrees of Freedom and Wigner Distribution.- 2.1 The Wigner Distribution.- 2.2 The Space Bandwidth Product (SW) as a Tool for Superresolution.- 3 The Concept of Superresolution.- 3.1 What Is Resolution?.- 3.2 Superresolution as SW Adaptation.- 4 Diffractive Superresolution.- 4.1 Superresolution Based on Temporal Constraints.- 4.2 Cyclostationary Gratings for Incoherent Optical Superresolution Systems.- 4.3 The Generalized Wigner Function for Analysis of Superresolution Systems.- 4.4 Superresolution for Objects with Finite Size.- 4.5 Wavelength Multiplexing Superresolution.- 5 Complex Adaptation.- 5.1 Alternative Adaptation Schemes.- 5.2 Novel Techniques for Obtaining Near Field Optical Superresolution.- 6 Geometrical Superresolution.- 6.1 Introduction.- 6.2 Geometrical Resolution.- 6.3 SW-Adaptation for Geometrical Superresolution.- 6.4 Geometrical Superresolution.- 6.5 Digital Superresolution with CDMA.- 7 Noise Equivalent Superresolution.- 7.1 Noise Equivalent Resolution.- 7.2 Relevance to Measured Quantities.- 8 Some Industrial Examples.- 8.1 Superresolving Ability for Detecting Point Targets.- 8.2 Superresolving Ability for Barcode Scanners.- 8.3 The Optimal System for Subwavelength Point Source Localization.