New prospects in line detection for remote sensing images
Nicolas Merlet, Josiane B. Zerubia · 2002
Dynamic programming is one of the main methods of line detection. It defines a cost, which depends on local information, and performs a summation-minimization process in a graph or in the image. In particular, Fischler et al. (1981) presented an algorithm called F*, which achieves important results (convergence, robustness, rapidity). In previous works, we proposed a mathematical formalization of the F*, which allowed us to extend the cost to cliques of more than two points to take into account the contrast, and to include curvature information in the cost by using neighborhoods of size larger than one. In the present paper, we propose a method for computing this cost automatically for a wide range of images, from the probability distribution in the neighborhood of sample segments. We apply the resulting potentials on SPOT images.>