Image Processing Using Pulse-Coupled Neural Networks
Lindblad, T.
Image Processing Using Pulse-Coupled Neural Networks [electronic resource] / by T. Lindblad, J.M. Kinser. - Second, Revised Edition. - XI, 164 p. 140 illus. online resource.
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.
9783540282938
10.1007/3-540-28293-9 doi
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 Engineering.
TK5102.9 TA1637-1638 TK7882.S65
621.382
Image Processing Using Pulse-Coupled Neural Networks [electronic resource] / by T. Lindblad, J.M. Kinser. - Second, Revised Edition. - XI, 164 p. 140 illus. online resource.
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.
9783540282938
10.1007/3-540-28293-9 doi
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 Engineering.
TK5102.9 TA1637-1638 TK7882.S65
621.382