Abstract
In this paper we introduce a neural network implementation of gray scale operators. In this structure, synaptic weights are represented by a gray scale structuring element and trained by a learning algorithm based on an optimal criterion called the overall equality index. It will be shown that the proposed algorithm leads to a computationally simple implementation. Numerical examples will be presented to illustrate its performance.
Original language | English |
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Pages (from-to) | 276-286 |
Number of pages | 11 |
Journal | Proceedings of SPIE - The International Society for Optical Engineering |
Volume | 1658 |
DOIs | |
Publication status | Published - 1992 Apr 1 |
Externally published | Yes |
Event | Nonlinear Image Processing III 1992 - San Jose, United States Duration: 1992 Feb 9 → 1992 Feb 14 |
ASJC Scopus subject areas
- Electronic, Optical and Magnetic Materials
- Condensed Matter Physics
- Computer Science Applications
- Applied Mathematics
- Electrical and Electronic Engineering