Statistical Inference for Spatial Processes
Statistical Inference for Spatial Processes
A Pyramid Framework for Early Vision: Multiresolutional Computer Vision
A Pyramid Framework for Early Vision: Multiresolutional Computer Vision
Environmental Modeling with GIS
Environmental Modeling with GIS
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
| Hi-index | 0.00 |
A previous study proposed a new model for generating random spatial patterns for modelling the dispersion of different colors in an image (Chiarello et al., 1996). These simulations represented spatial structures in the sense of landscape ecology and they had to be compared to a real image. Thus, the aim of the present study was to measure the discrepancy between a set of simulations of multicolored mosaics and an observed pattern in order to build a Monte Carlo test. The multicolored mosaics were considered as random closed sets and described with the hitting function for all pairs of colors. This description provided large three-dimensional data tables (distances × color pairs × images) that were analyzed with the help of multiway data analyses. The partial triadic analysis was used. It provided a synthesis of the hitting function since the intrastructure enabled a typology of the distances for each image: the factorial coordinates of supplementary columns were plotted as ordinates against distances as abscissa. This synthetic descriptor provided a graphic tool for measuring the differences between the spatial dispersions of a same set of colors in several images.