In this paper an image enhancing technique is described. It is based on Shunting Inhibitory Cellular Neural Networks (SICNN). As the limitation of the linear approaches to image coding, enhancement, and feature extraction became apparent, research in image processing began to disperse into the three goal-driven directions. However Shunting Inhibitory Cellular Neural Networks model simultaneously addresses the three problems of coding, enhancement, and extraction, as it acts to compress the dynamic range, reorganize the signal to improve visibility, suppress noise, and identify local features. The algorithm we are describing is simple and cost-effective, and can be easily applied in real-time processing for digital still camera application
A new Cellular Neural Network model is proposed which allows simpler and faster VLSI implementation ...
A few years ago, Tsuruta et al. have proposed Direction-Preserving Small World Cellular Neural Netwo...
Utilization of artificial neural networks in digital image processing is nothing new. The aim of thi...
Shunting inhibition is a model of early visual processing which can provide contrast and edge enhanc...
A novel read-out and column circuit for VLSI implementation of a Shunting Inhibition Cellular Neural...
Novel image enhancement technique using shunting inhibitory cellular neural network
Bibliographical references: p. 225-234.xxiv, 285 p. : ill. ; 30 cm.Thesis (Ph.D.)--University of Ade...
Biologically inspired shunting inhibition-based processing is shown to improve significantly the per...
Biologically inspired shunting inhibition-based processing is shown to improve significantly the per...
In this paper a real-time mixed analog-digital VLSI implementation of a Shunting Inhibition Cellular...
Abstract—Cellular neural network (CNN) is a large-scale nonlinear analog circuit suitable for real-t...
Bi-i (Bio-inspired) Cellular Vision system is built mainly on Cellular Neural /Nonlinear Networks (C...
In this paper, a novel analog retinomorphic block performing the edge enhancing and edge detection c...
A few years ago, Tsuruta et al. have proposed Small World Cellular Neural Networks (SWCNN). SWCNN is...
Abstract: In this contribution, we propose the use of Cellular Neural Networks as an application for...
A new Cellular Neural Network model is proposed which allows simpler and faster VLSI implementation ...
A few years ago, Tsuruta et al. have proposed Direction-Preserving Small World Cellular Neural Netwo...
Utilization of artificial neural networks in digital image processing is nothing new. The aim of thi...
Shunting inhibition is a model of early visual processing which can provide contrast and edge enhanc...
A novel read-out and column circuit for VLSI implementation of a Shunting Inhibition Cellular Neural...
Novel image enhancement technique using shunting inhibitory cellular neural network
Bibliographical references: p. 225-234.xxiv, 285 p. : ill. ; 30 cm.Thesis (Ph.D.)--University of Ade...
Biologically inspired shunting inhibition-based processing is shown to improve significantly the per...
Biologically inspired shunting inhibition-based processing is shown to improve significantly the per...
In this paper a real-time mixed analog-digital VLSI implementation of a Shunting Inhibition Cellular...
Abstract—Cellular neural network (CNN) is a large-scale nonlinear analog circuit suitable for real-t...
Bi-i (Bio-inspired) Cellular Vision system is built mainly on Cellular Neural /Nonlinear Networks (C...
In this paper, a novel analog retinomorphic block performing the edge enhancing and edge detection c...
A few years ago, Tsuruta et al. have proposed Small World Cellular Neural Networks (SWCNN). SWCNN is...
Abstract: In this contribution, we propose the use of Cellular Neural Networks as an application for...
A new Cellular Neural Network model is proposed which allows simpler and faster VLSI implementation ...
A few years ago, Tsuruta et al. have proposed Direction-Preserving Small World Cellular Neural Netwo...
Utilization of artificial neural networks in digital image processing is nothing new. The aim of thi...