Parameter estimation, multiscale representation and algorithms for energy-minimizing segmentations

The author analyzes basic problems of image segmentation-edge detection, elimination of weak boundaries and small segments, and multiscale representation-in the context of all energy-minimizing model. He discusses two general frameworks for finding approximate solutions, the split-and-merge algorithm based on energy criteria, and nonlinear diffusion. The difficulty with the split-and-merge algorithm considered is that unless further approximations are introduced, it does not have an easy parallel implementation. The idea of the alternative approach, based on nonlinear diffusion, is to produce first only a blurred version of the discontinuities of f (the smoothed image which need not be continuous across the segmenting curve) in the hope of controlling the extent of the smoothing of small domains and then to refine the approximate solution by the method of steepest descent. Thus, the method sets thresholds only indirectly