Coupled Geometry-Driven Diffusion Equations for Low-Level Vision

This chapter introduces a number of systems of coupled, nonlinear diffusion equations and investigates their role in noise suppression and edge-preserving smoothing. The basic idea is that several maps describing the image, undergo coupled development towards an equilibrium state, repre- senting the enhanced image. These maps could e.g. contain intensity, local edge strength, range, or another quantity. All these maps, including the edge map, contain continuous rather than all-or-nothing information, following a strategy of least commitment. Each of the approaches has been developed and tested on a parallel transputer network.