Image Processing Using Pulse-Coupled Neural Networks [electronic resource] / by T. Lindblad, J.M. Kinser.

By: Lindblad, T [author.]Contributor(s): Kinser, J.M [author.] | SpringerLink (Online service)Material type: TextTextLanguage: English Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2005Edition: Second, Revised EditionDescription: XI, 164 p. 140 illus. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783540282938Subject(s): Engineering | Physical optics | Biomedical engineering | Mathematical statistics | Surfaces (Physics) | Engineering | Signal, Image and Speech Processing | Surfaces and Interfaces, Thin Films | Applied Optics, Optoelectronics, Optical Devices | Biophysics/Biomedical Physics | Statistical Theory and Methods | Physics and Applied Physics in EngineeringAdditional physical formats: Printed edition:: No titleDDC classification: 621.382 LOC classification: TK5102.9TA1637-1638TK7882.S65Online resources: Click here to access online
Contents:
and Theory -- Theory of Digital Simulation -- Automated Image Object Recognition -- Image Fusion -- Image Texture Processing -- Image Signatures -- Miscellaneous Applications -- Hardware Implementations.
In: Springer eBooksSummary: This is the first book to explain and demonstrate the tremendous ability of Pulse-Coupled Neural Networks (PCNNs) when applied to the field of image processing. PCNNs and their derivatives are biologically inspired models that are powerful tools for extracting texture, segments, and edges from images. As these attributes form the foundations of most image processing tasks, the use of PCNNs facilitates traditional tasks such as recognition, foveation, and image fusion. PCNN technology has also paved the way for new image processing techniques such as object isolation, spiral image fusion, image signatures, and content-based image searches. This volume contains examples of several image processing applications, as well as a review of hardware implementations.
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and Theory -- Theory of Digital Simulation -- Automated Image Object Recognition -- Image Fusion -- Image Texture Processing -- Image Signatures -- Miscellaneous Applications -- Hardware Implementations.

This is the first book to explain and demonstrate the tremendous ability of Pulse-Coupled Neural Networks (PCNNs) when applied to the field of image processing. PCNNs and their derivatives are biologically inspired models that are powerful tools for extracting texture, segments, and edges from images. As these attributes form the foundations of most image processing tasks, the use of PCNNs facilitates traditional tasks such as recognition, foveation, and image fusion. PCNN technology has also paved the way for new image processing techniques such as object isolation, spiral image fusion, image signatures, and content-based image searches. This volume contains examples of several image processing applications, as well as a review of hardware implementations.

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