CONICET | Buscador de Institutos y Recursos Humanos

We present a new method for computing the local fractal dimension in remote sensing imagery. It is based on an estimation of the quadratic self correlation (or 2D Hurst coefficient) of the luminance. The method is thoroughly tested with a set of synthetic images. A comparison to other local fractal dimension estimators is presented. Also, remote sensing imagery was used to assess the usefulness of the techniques for image segmentation. Quadratic self correlation methods provided more accurate results with synthetic images, and also produced more robust and fit segmentations in remote sensing imagery. Even with very small computation windows, the methods proved to be able to detect borders and minutiae precisely.