Logic Based Nonlinear Image Processing

This text provides insight into the design of optimal image processing operators for implementation directly into digital hardware. Starting with simple restoration examples and using the minimum of statistics, the book provides a design strategy for a wide range of image processing applications. The text is aimed principally at electronics engineers and computer scientists, but will also be of interest to anyone working with digital images.

Abstract: This text provides insight into the design of optimal image processing operators for implementation directly into digital hardware. Starting with simple restoration examples and using the minimum of statistics, the book provides a design strategy for a wide range of image processing applications. The text is aimed principally at electronics engineers and computer scientists, but will also be of interest to anyone working with digital images.

From a strict semantic point of view, nonlinear image processing encompasses all image processing that is not based on linear operators; however, from a practical, evolutionary point of view, the name itself is usually associated with the study of nonlinear filters, mainly the deterministic and nondeterministic analysis and design of logic-based operators. This Tutorial Text volume explores logic-based operators with emphasis on representation, design, and statistical optimization of nonlinear filters.

This state-of-the-art book deals with the most important aspects of non-linear imaging challenges. The need for engineering and mathematical methods is essential for defining non-linear effects involved in such areas as computer vision, optical imaging, computer pattern recognition, and industrial automation challenges.

Mathematical Nonlinear Image Processing deals with a fast growing research area. The development of the subject springs from two factors: (1) the great expansion of nonlinear methods applied to problems in imaging and vision, and (2) the degree to which nonlinear approaches are both using and fostering new developments in diverse areas of mathematics. Mathematical Nonlinear Image Processing will be of interest to people working in the areas of applied mathematics as well as researchers in computer vision. Mathematical Nonlinear Image Processing is an edited volume of original research. It has also been published as a special issue of the Journal of Mathematical Imaging and Vision. (Volume 2, Issue 2/3).

Advances in Imaging and Electron Physics features cutting-edge articles on the physics of electron devices (especially semiconductor devices), particle optics at high and low energies, microlithography, image science and digital image processing, electromagnetic wave propagation, electron microscopy, and the computing methods used in all these domains. Contributions from leading authorities Informs and updates on all the latest developments in the field

Offers an introduction to the subject of radiation thermometry, focusing on sources of measurement error and giving advice on methods for minimizing or eliminating these errors. This title cover such topics as: blackbody radiation, emissivity, reflection errors, and atmospheric absorption and emission; and common radiation thermometers.

Ten years after the publication of Infrared Optics and Zoom Lenses, this text is still the only current publication devoted exclusively to infrared zoom lenses. This updated second edition includes 18 new refractive and reflective infrared zoom systems, bringing the total number of infrared zoom optical systems to 41 systems. Other additions include a section on focal plane arrays and a new closing chapter specifically devoted to applications of infrared zoom lenses. Coverage of wavelength region has been expanded to include the near infrared. Additional topics include an examination of the importance of principal planes, methods for athermalization by means of computer glass substitution, and global optimization techniques for zoom lens design.