Abstract
The two-dimensional Anisotropic Wavelet Transform aims to decipher images in which distributions are combined at different scales. Based on the Optimized Anisotropic Wavelet Coefficient method (OAWC), we present two C ++ programs which enable multi-scale analysis and discrimination of objects, or groups of objects, depending on their area, shape ratio, orientation, and location. These programs allow the identification of the different levels of organization that are present in an image (objects, clusters, alignments of clusters), and the quantification of their sizes, shape ratios, and orientations. The programs run on a standard IBM-PC. A complete analysis, performed on a constructed image, is presented as an example for its graphical results, and illustrates the potential of quantifying the anisotropies of orientation, shape, and spatial distribution of organized structures at different scales.
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