Abstract.
We are interested in diffusion PDE ’s for smoothing multi-valued im- ages in an anisotropic manner. By pointing out the pros and cons of existing tensor-driven regularization methods, we introduce a new constrained diffusion PDE that regularizes image data while taking curvatures of image structures into account. Our method has a direct link with a continuous formulation of the Line Integral Convolutions, allowing us to design a very fast and stable algorithm for its implementation. Besides, our smoothing scheme numerically performs with a sub-pixel accuracy and is then able to preserves very thin image structures con- trary to classical PDE discretizations based on finite difference approximations. We illustrate our method with different applications on color images.