Orientation Diffusions

Abstract

Diffusions provide a convenient way of smoothing noisy brightness images, of analyzing images at multiple scales, and of enhancing discontinuities. Some quantities of interest in computer vision are defined on curved manifolds; typical examples are orientation and hue that are defined on the circle. Generalizing diffusions to orientation is not straightforward, especially in the case where a discrete implementation is sought. An example of what may go wrong is presented. A method is proposed to define diffusions of orientation-like quantities. First a definition in the continuum is discussed, then a discrete orientation diffusion is proposed. The behavior of such diffusions is explored both analytically and experimentally. It is shown how such orientation diffusions contain a nonlinearity that is reminiscent of edge-process and anisotropic diffusion. A number of open questions are proposed at the end.