학술논문

A network of networks processing model for image regularization
Document Type
Periodical
Source
IEEE Transactions on Neural Networks IEEE Trans. Neural Netw. Neural Networks, IEEE Transactions on. 8(1):169-174 Jan, 1997
Subject
Computing and Processing
Communication, Networking and Broadcast Technologies
Degradation
Parallel processing
Sensor arrays
Pixel
Optimization methods
Computer networks
Biological system modeling
Computer architecture
Hardware
Pattern analysis
Language
ISSN
1045-9227
1941-0093
Abstract
We introduce a network of networks (NoN) model to solve image regularization problems. The method is motivated by the fact that natural image formation involves both local processing and globally coordinated parallel processing. Both forms are readily implemented using an NoN architecture. The modeling is very powerful in that it achieves high-quality adaptive processing, and it reduces the computational difference between inhomogeneous and homogeneous conditions. This method is able to provide fast, quality imaging in early vision, and its replicating structure and sparse connectivity readily lend themselves to hardware implementations.