Color Image Segmentation Based on Vectorial Multiscale Diffusion with Inter-scale Linking

Abstract

We propose a segmentation scheme for digital color images using vectorial multiscale anisotropic diffusion. By integrating the edge information, diffusion based schemes can remove noise effectively and create fine to coarse set of images known as scale-space. Segmentation is performed by effectively tracking edges in an inter-scale manner across this scale space family of images. The regions are connected according to color coherency, and scale relation along time axis of the family is taken into account for the final segmentation result. Fast total variation diffusion and anisotropic diffusion facilitate denoising and create homogenous regions separated by strong edges. They provide a roadmap for further segmentation with persistent edges and flat regions. The scheme is general in the sense that other anisotropic diffusion schemes can be incorporated depending upon the requirement. Numerical simulations show the advantage of the proposed scheme on noisy color images.