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Nonlinear Image Processing

Nonlinear Image Processing

Giovanni Sicuranza | Sanjit Mitra

(2000)

Abstract

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.

  • Presents the latest developments in a variety of filter design techniques and algorithms
  • Contains essential information for development of Human Vision Systems (HVS)
  • Provides foundations for digital imaging and image capture technology

"The book considers the following filter families, with varying emphasis, according to popularity and impact in image processing tasks:
  • honomorphic filters, relying on a generalized superposition principle
  • nonlinear mean filters, using nonlinear definitions of means
  • morphological filters, based on geometrical rather than analytical properties
  • order statistics filters, based on ordering properties of the input samples
  • polynomial filters, using polynomial expressions in the input and output samples
  • fuzzy filters, applying fuzzy reasoning to model the uncertainty typical of some image processing issues
  • nonlinear operations modeled in terms of nonlinear partial differential equations."
--IEEE SIGNAL PROCESSING MAGAZINE, January 2001