This paper deals with digital patterns generated by a class of random geometric processes proposed as models for images. The joint gray-level probability density for pairs of points at given separations is used to derive various second-order image statistics, including the autocorrelation, edge density, and variogram. In modeling images using these processes, these results can be used for fitting models to a given ensemble of images.
ASJC Scopus subject areas
- Control and Systems Engineering
- Theoretical Computer Science
- Computer Science Applications
- Information Systems and Management
- Artificial Intelligence