  This paper proposes an efficient probabilistic method that computes
combinatorial gradient fields for two dimensional image data. In contrast to
existing algorithms, this approach yields a geometric Morse-Smale complex that
converges almost surely to its continuous counterpart when the image resolution
is increased. This approach is motivated using basic ideas from probability
theory and builds upon an algorithm from discrete Morse theory with a strong
mathematical foundation. While a formal proof is only hinted at, we do provide
a thorough numerical evaluation of our method and compare it to established
algorithms.
