Hierarchical segmentation using dynamics of multiscale color gradient watersheds

In this paper, we describe and compare two multiscale color segmentation schemes based on the Gaussian multiscale and the Perona and Malik anisotropic diffusion. The proposed segmentation schemes consist of an extension to color images of an earlier multiscale hierarchical watershed segmentation for scalar images. Our segmentation scheme constructs a hierarchy among the watershed regions using the principle of dynamics of contours in scale-space. Each contour is valuated by combining the dynamics of contours over the successive scales. We conduct experiments on the scale-space stacks created by the Gaussian scale-space and the Perona and Malik anisotropic diffusion scheme. Our experimental results consist of the comparison of both schemes with respect to the following aspects: size and information reduction between successive levels of the hierarchical stack, dynamics of contours in scale space and computation time.